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Wei YH, Lin F. Barcodes based on nucleic acid sequences: Applications and challenges (Review). Mol Med Rep 2025; 32:187. [PMID: 40314098 PMCID: PMC12076290 DOI: 10.3892/mmr.2025.13552] [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: 10/22/2024] [Accepted: 03/04/2025] [Indexed: 05/03/2025] Open
Abstract
Cells are the fundamental structural and functional units of living organisms and the study of these entities has remained a central focus throughout the history of biological sciences. Traditional cell research techniques, including fluorescent protein tagging and microscopy, have provided preliminary insights into the lineage history and clonal relationships between progenitor and descendant cells. However, these techniques exhibit inherent limitations in tracking the full developmental trajectory of cells and elucidating their heterogeneity, including sensitivity, stability and barcode drift. In developmental biology, nucleic acid barcode technology has introduced an innovative approach to cell lineage tracing. By assigning unique barcodes to individual cells, researchers can accurately identify and trace the origin and differentiation pathways of cells at various developmental stages, thereby illuminating the dynamic processes underlying tissue development and organogenesis. In cancer research, nucleic acid barcoding has played a pivotal role in analyzing the clonal architecture of tumor cells, exploring their heterogeneity and resistance mechanisms and enhancing our understanding of cancer evolution and inter‑clonal interactions. Furthermore, nucleic acid barcodes play a crucial role in stem cell research, enabling the tracking of stem cells from diverse origins and their derived progeny. This has offered novel perspectives on the mechanisms of stem cell self‑renewal and differentiation. The present review presented a comprehensive examination of the principles, applications and challenges associated with nucleic acid barcode technology.
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Affiliation(s)
- Ying Hong Wei
- Department of Clinical Laboratory, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, P.R. China
- State Key Laboratory of Targeting Oncology, National Center for International Research of Bio-targeting Theranostics, Guangxi Key Laboratory of Bio-targeting Theranostics, Collaborative Innovation Center for Targeting Tumor Diagnosis and Therapy, Guangxi Medical University, Nanning, Guangxi 530021, P.R. China
| | - Faquan Lin
- Department of Clinical Laboratory, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, P.R. China
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2
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Bavais J, Chevallier J, Spinelli L, van de Pavert S, Puthier D. SciGeneX: enhancing transcriptional analysis through gene module detection in single-cell and spatial transcriptomics data. NAR Genom Bioinform 2025; 7:lqaf043. [PMID: 40248490 PMCID: PMC12004220 DOI: 10.1093/nargab/lqaf043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2024] [Revised: 03/19/2025] [Accepted: 04/09/2025] [Indexed: 04/19/2025] Open
Abstract
The standard pipeline to analyze single-cell RNA-seq or spatial transcriptomics data focuses on a gene-centric approach that overlooks the collective behavior of genes. However, understanding cell populations necessitates recognizing intricate combinations of activated and repressed pathways. Therefore, a broader view of gene behavior offers more accurate insights into cellular heterogeneity in single-cell or spatial transcriptomics data. Here, we describe SciGeneX (Single-cell informative Gene eXplorer), a R package implementing a neighborhood analysis and a graph partitioning method to generate co-expression gene modules. These modules, whether shared or restricted to cell populations, collectively reflect cellular heterogeneity. Their combinations are able to highlight specific cell populations, even rare ones. SciGeneX uncovers rare and novel cell populations that were not observed before in human thymus spatial transcriptomics data. We show that SciGeneX outperforms existing methods on both artificial and experimental datasets. Overall, SciGeneX will aid in unravelling cellular and molecular diversity in single-cell and spatial transcriptomics studies.
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Affiliation(s)
- Julie Bavais
- Aix-Marseille Univ, INSERM, TAGC, Turing Centre for Living systems, 13288 Marseille, France
- Aix-Marseille Univ, CNRS, INSERM, CIML, Turing Centre for Living systems, 13009 Marseille, France
| | - Jessica Chevallier
- Aix-Marseille Univ, INSERM, TAGC, Turing Centre for Living systems, 13288 Marseille, France
- Aix-Marseille Univ, CNRS, INSERM, CIML, Turing Centre for Living systems, 13009 Marseille, France
| | - Lionel Spinelli
- Aix-Marseille Univ, INSERM, TAGC, Turing Centre for Living systems, 13288 Marseille, France
- Aix-Marseille Univ, CNRS, INSERM, CIML, Turing Centre for Living systems, 13009 Marseille, France
| | - Serge A van de Pavert
- Aix-Marseille Univ, CNRS, INSERM, CIML, Turing Centre for Living systems, 13009 Marseille, France
| | - Denis Puthier
- Aix-Marseille Univ, INSERM, TAGC, MarMaRa Institute, Turing Centre for Living systems, Transcriptomics and Genomics Marseille Luminy (TGML), 13288 Marseille, France
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3
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Weidling I, Preiss CN, Chancellor SE, Srivastava G, Gibilisco L, Lin G, Brennan MS, Lee J, Roth LM, Morozova O, Nam KN, Patel NR, Liu Q, Thomas JK, Reinhardt P, Wilkens R, Ehrnhoefer DE, Striebinger A, Barghorn S, Xanthopoulos C, Weil MT, Biesinger S, Cik M, Romanul N, Yanamandra K, Welker AM, Wu J, Gasparini L, Stöhr J, Langlois X, Manos JD. hiPSC-neurons recapitulate the subtype-specific cell intrinsic nature of susceptibility to neurodegenerative disease-relevant aggregation. Acta Neuropathol Commun 2025; 13:108. [PMID: 40390134 PMCID: PMC12087151 DOI: 10.1186/s40478-025-02000-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2024] [Accepted: 04/05/2025] [Indexed: 05/21/2025] Open
Abstract
Alzheimer's disease (AD) is characterized by the accumulation and spread of Tau intraneuronal inclusions throughout most of the telencephalon, leaving hindbrain regions like the cerebellum and spinal cord largely spared. These neuropathological observations, along with the identification of specific vulnerable sub-populations from AD brain-derived single nuclei transcriptomics, suggest that a subset of brain regions and neuronal subtypes possess a selective vulnerability to Tau pathology. Given the inability to culture neurons from patient brains, a disease-relevant in vitro model which recapitulates these features would serve as a critical tool to validate modulators of vulnerability and resilience. Using our recently established platform for inducing endogenous Tau aggregation in human induced pluripotent stem cell (hiPSC)-derived cortical excitatory neurons via application of AD brain-derived exogenous Tau aggregates, we explored whether Tau aggregates preferentially induce aggregation in specific neuronal subtypes. We compared Tau seeding in hiPSC-derived neuron subtypes representing regional identities across the forebrain, midbrain, and hindbrain. Higher susceptibility (i.e. more Tau aggregation) was consistently observed among cortical neuron subtypes, with CTIP2-positive, somatostatin (SST)-positive cortical inhibitory neurons showing the greatest aggregation levels across hiPSC lines from multiple donors. hiPSC-neurons also delineated between the disease-specific vulnerabilities of different protein aggregates, as α-synuclein preformed fibrils showed an increased propensity to induce aggregates in midbrain dopaminergic (mDA)-like neurons, mimicking Parkinson's disease (PD)-specific susceptibility. Aggregate uptake and degradation rates were insufficient to explain differential susceptibility. The absence of a consistent transcriptional response following aggregate seeding further indicated that intrinsic neuronal subtype-specific properties could drive susceptibility. The present data provides evidence that hiPSC-neurons exhibit features of selective neuronal vulnerability which manifest in a cell autonomous manner, suggesting that mining intrinsic (or basal) transcriptomic signatures of more vulnerable compared to more resilient hiPSC-neurons could uncover the molecular underpinnings of differential susceptibility to protein aggregation found in a variety of neurodegenerative diseases.
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Affiliation(s)
- Ian Weidling
- AbbVie, Cambridge Research Center, 200 Sidney Street, Cambridge, MA, 02139, USA
| | - Christina N Preiss
- AbbVie, Cambridge Research Center, 200 Sidney Street, Cambridge, MA, 02139, USA
| | - Sarah E Chancellor
- AbbVie, Cambridge Research Center, 200 Sidney Street, Cambridge, MA, 02139, USA
| | - Gyan Srivastava
- AbbVie, Cambridge Research Center, 200 Sidney Street, Cambridge, MA, 02139, USA
| | - Lauren Gibilisco
- AbbVie, Cambridge Research Center, 200 Sidney Street, Cambridge, MA, 02139, USA
| | - Gen Lin
- AbbVie Pte Ltd, 9 North Buona Vista Drive #19-01, Singapore, 138588, Singapore
| | | | - Janice Lee
- AbbVie, Cambridge Research Center, 200 Sidney Street, Cambridge, MA, 02139, USA
| | - Lindsay M Roth
- AbbVie, Cambridge Research Center, 200 Sidney Street, Cambridge, MA, 02139, USA
| | - Olga Morozova
- AbbVie, Cambridge Research Center, 200 Sidney Street, Cambridge, MA, 02139, USA
| | - Kyong Nyon Nam
- AbbVie, Cambridge Research Center, 200 Sidney Street, Cambridge, MA, 02139, USA
| | - Nehal R Patel
- AbbVie, Cambridge Research Center, 200 Sidney Street, Cambridge, MA, 02139, USA
| | - Qing Liu
- AbbVie, Cambridge Research Center, 200 Sidney Street, Cambridge, MA, 02139, USA
| | | | - Peter Reinhardt
- AbbVie Deutschland GmbH & Co. KG, 67061, Ludwigshafen, Germany
| | - Ruven Wilkens
- AbbVie Deutschland GmbH & Co. KG, 67061, Ludwigshafen, Germany
| | | | | | - Stefan Barghorn
- AbbVie Deutschland GmbH & Co. KG, 67061, Ludwigshafen, Germany
| | | | | | | | - Miroslav Cik
- AbbVie Deutschland GmbH & Co. KG, 67061, Ludwigshafen, Germany
| | - Nandini Romanul
- AbbVie, Cambridge Research Center, 200 Sidney Street, Cambridge, MA, 02139, USA
| | - Kiran Yanamandra
- AbbVie, Cambridge Research Center, 200 Sidney Street, Cambridge, MA, 02139, USA
| | - Alessandra M Welker
- AbbVie, Cambridge Research Center, 200 Sidney Street, Cambridge, MA, 02139, USA
| | - Jessica Wu
- AbbVie, Cambridge Research Center, 200 Sidney Street, Cambridge, MA, 02139, USA
| | - Laura Gasparini
- AbbVie Deutschland GmbH & Co. KG, 67061, Ludwigshafen, Germany
| | - Jan Stöhr
- AbbVie, Cambridge Research Center, 200 Sidney Street, Cambridge, MA, 02139, USA
| | - Xavier Langlois
- AbbVie, Cambridge Research Center, 200 Sidney Street, Cambridge, MA, 02139, USA
| | - Justine D Manos
- AbbVie, Cambridge Research Center, 200 Sidney Street, Cambridge, MA, 02139, USA.
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Arya A, Tripathi P, Dubey N, Aier I, Kumar Varadwaj P. Navigating single-cell RNA-sequencing: protocols, tools, databases, and applications. Genomics Inform 2025; 23:13. [PMID: 40382658 DOI: 10.1186/s44342-025-00044-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2025] [Accepted: 04/07/2025] [Indexed: 05/20/2025] Open
Abstract
Single-cell RNA-sequencing (scRNA-seq) technology brought about a revolutionary change in the transcriptomic world, paving the way for comprehensive analysis of cellular heterogeneity in complex biological systems. It enabled researchers to see how different cells behaved at single-cell levels, providing new insights into the process. However, despite all these advancements, scRNA-seq also experiences challenges related to the complexity of data analysis, interpretation, and multi-omics data integration. In this review, these complications were discussed in detail, directly pointing at the optimization of scRNA-seq approaches and understanding the world of single-cell and its dynamics. Different protocols and currently functional single-cell databases were also covered. This review highlights different tools for the analysis of scRNA-seq and their methodologies, emphasizing innovative techniques that enhance resolution and accuracy at a single-cell level. Various applications were explored across domains including drug discovery, tumor microenvironment (TME), biomarker discovery, and microbial profiling, and case studies were discussed to explain the importance of scRNA-seq by uncovering novel and rare cell types and their identification. This review underlines a crucial aspect of scRNA-seq in the advancement of personalized medicine and highlights its potential to understand the complexity of biological systems.
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Affiliation(s)
- Ankish Arya
- Department of Applied Sciences, Indian Institute of Information Technology Allahabad, Jhalwa, Prayagraj, 211015, Uttar Pradesh, India
| | - Prabhat Tripathi
- Department of Applied Sciences, Indian Institute of Information Technology Allahabad, Jhalwa, Prayagraj, 211015, Uttar Pradesh, India
| | - Nidhi Dubey
- Department of Applied Sciences, Indian Institute of Information Technology Allahabad, Jhalwa, Prayagraj, 211015, Uttar Pradesh, India
| | - Imlimaong Aier
- Department of Applied Sciences, Indian Institute of Information Technology Allahabad, Jhalwa, Prayagraj, 211015, Uttar Pradesh, India
| | - Pritish Kumar Varadwaj
- Department of Applied Sciences, Indian Institute of Information Technology Allahabad, Jhalwa, Prayagraj, 211015, Uttar Pradesh, India.
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Yu G, Li J, Zhang H, Zi H, Liu M, An Q, Qiu T, Li P, Song J, Liu P, Quan K, Li S, Liu Y, Zhu W, Du J. Single-cell analysis reveals the implication of vascular endothelial cell-intrinsic ANGPT2 in human intracranial aneurysm. Cardiovasc Res 2025; 121:658-673. [PMID: 39187926 DOI: 10.1093/cvr/cvae186] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Revised: 05/04/2024] [Accepted: 06/13/2024] [Indexed: 08/28/2024] Open
Abstract
AIMS While previous single-cell RNA sequencing (scRNA-seq) studies have attempted to dissect intracranial aneurysm (IA), the primary molecular mechanism for IA pathogenesis remains unknown. Here, we uncovered the alterations of cellular compositions, especially the transcriptome changes of vascular endothelial cells (ECs), in human IA. METHODS AND RESULTS We performed scRNA-seq to compare the cell atlas of sporadic IA and the control artery. The transcriptomes of 43 462 cells were profiled for further analysis. In general, IA had increased immune cells (T/NK cells, B cells, myeloid cells, mast cells, neutrophils) and fewer vascular cells (ECs, vascular smooth muscle cells, and fibroblasts). Based on the obtained high-quantity and high-quality EC data, we found genes associated with angiogenesis in ECs from IA patients. By EC-specific expression of candidate genes in vivo, we observed the involvement of angpt2a in causing cerebral vascular abnormality. Furthermore, an IA zebrafish model mimicking the main features of human IA was generated through targeting pdgfrb gene, and knockdown of angpt2a alleviated the vascular dilation in the IA zebrafish model. CONCLUSION By performing a landscape view of the single-cell transcriptomes of IA and the control artery, we contribute to a deeper understanding of the cellular composition and the molecular changes of ECs in IA. The implication of angiogenic regulator ANGPT2 in IA formation and progression, provides a novel potential therapeutical target for IA interventions.
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Affiliation(s)
- Guo Yu
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, 12 Middle Wulumuqi Road, Shanghai 200040, China
- National Center for Neurological Disorders, 12 Middle Wulumuqi Road, Shanghai 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Neurosurgical Institute of Fudan University, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Shanghai Clinical Medical Center of Neurosurgery,12 Middle Wulumuqi Road, Shanghai 200040, China
| | - Jia Li
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai 200031, China
| | - Hongfei Zhang
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, 12 Middle Wulumuqi Road, Shanghai 200040, China
- National Center for Neurological Disorders, 12 Middle Wulumuqi Road, Shanghai 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Neurosurgical Institute of Fudan University, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Shanghai Clinical Medical Center of Neurosurgery,12 Middle Wulumuqi Road, Shanghai 200040, China
| | - Huaxing Zi
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai 200031, China
- University of Chinese Academy of Sciences, 19A Yu-Quan Road, Beijing 100049, China
| | - Mingjian Liu
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, 12 Middle Wulumuqi Road, Shanghai 200040, China
- National Center for Neurological Disorders, 12 Middle Wulumuqi Road, Shanghai 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Neurosurgical Institute of Fudan University, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Shanghai Clinical Medical Center of Neurosurgery,12 Middle Wulumuqi Road, Shanghai 200040, China
| | - Qingzhu An
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, 12 Middle Wulumuqi Road, Shanghai 200040, China
- National Center for Neurological Disorders, 12 Middle Wulumuqi Road, Shanghai 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Neurosurgical Institute of Fudan University, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Shanghai Clinical Medical Center of Neurosurgery,12 Middle Wulumuqi Road, Shanghai 200040, China
| | - Tianming Qiu
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, 12 Middle Wulumuqi Road, Shanghai 200040, China
- National Center for Neurological Disorders, 12 Middle Wulumuqi Road, Shanghai 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Neurosurgical Institute of Fudan University, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Shanghai Clinical Medical Center of Neurosurgery,12 Middle Wulumuqi Road, Shanghai 200040, China
| | - Peiliang Li
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, 12 Middle Wulumuqi Road, Shanghai 200040, China
- National Center for Neurological Disorders, 12 Middle Wulumuqi Road, Shanghai 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Neurosurgical Institute of Fudan University, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Shanghai Clinical Medical Center of Neurosurgery,12 Middle Wulumuqi Road, Shanghai 200040, China
| | - Jianping Song
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, 12 Middle Wulumuqi Road, Shanghai 200040, China
- National Center for Neurological Disorders, 12 Middle Wulumuqi Road, Shanghai 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Neurosurgical Institute of Fudan University, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Shanghai Clinical Medical Center of Neurosurgery,12 Middle Wulumuqi Road, Shanghai 200040, China
| | - Peixi Liu
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, 12 Middle Wulumuqi Road, Shanghai 200040, China
- National Center for Neurological Disorders, 12 Middle Wulumuqi Road, Shanghai 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Neurosurgical Institute of Fudan University, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Shanghai Clinical Medical Center of Neurosurgery,12 Middle Wulumuqi Road, Shanghai 200040, China
| | - Kai Quan
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, 12 Middle Wulumuqi Road, Shanghai 200040, China
- National Center for Neurological Disorders, 12 Middle Wulumuqi Road, Shanghai 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Neurosurgical Institute of Fudan University, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Shanghai Clinical Medical Center of Neurosurgery,12 Middle Wulumuqi Road, Shanghai 200040, China
| | - Sichen Li
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, 12 Middle Wulumuqi Road, Shanghai 200040, China
- National Center for Neurological Disorders, 12 Middle Wulumuqi Road, Shanghai 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Neurosurgical Institute of Fudan University, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Shanghai Clinical Medical Center of Neurosurgery,12 Middle Wulumuqi Road, Shanghai 200040, China
| | - Yingjun Liu
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, 12 Middle Wulumuqi Road, Shanghai 200040, China
- National Center for Neurological Disorders, 12 Middle Wulumuqi Road, Shanghai 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Neurosurgical Institute of Fudan University, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Shanghai Clinical Medical Center of Neurosurgery,12 Middle Wulumuqi Road, Shanghai 200040, China
| | - Wei Zhu
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, 12 Middle Wulumuqi Road, Shanghai 200040, China
- National Center for Neurological Disorders, 12 Middle Wulumuqi Road, Shanghai 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Neurosurgical Institute of Fudan University, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Shanghai Clinical Medical Center of Neurosurgery,12 Middle Wulumuqi Road, Shanghai 200040, China
| | - Jiulin Du
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai 200031, China
- University of Chinese Academy of Sciences, 19A Yu-Quan Road, Beijing 100049, China
- School of Life Science and Technology, ShanghaiTech University, 319 Yue-Yang Road, Shanghai 200031, China
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Leibovich N, Goyal S. Limitations and optimizations of cellular lineages tracking. PLoS Comput Biol 2025; 21:e1012880. [PMID: 40228207 PMCID: PMC11996212 DOI: 10.1371/journal.pcbi.1012880] [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: 10/07/2024] [Accepted: 02/14/2025] [Indexed: 04/16/2025] Open
Abstract
Tracking cellular lineages using genetic barcodes provides insights across biology and has become an important tool. However, barcoding strategies remain ad hoc. We show that elevating barcode insertion probability and thus increasing the average number of barcodes within the cells, adds to the number of traceable lineages but may decrease the accuracy of lineages inference due to reading errors. We establish the trade-off between accuracy in tracing lineages and the total number of traceable lineages, and find optimal experimental parameters under limited resources concerning the populations size of tracked cells and barcode pool complexity.
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Affiliation(s)
- Nava Leibovich
- NRC-Fields Mathematical Sciences Collaboration Centre, National Research Council of Canada, Toronto, Ontario, Canada
- Department of Physics, University of Toronto, Toronto, Ontario, Canada
| | - Sidhartha Goyal
- Department of Physics, University of Toronto, Toronto, Ontario, Canada
- Institute for Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada
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Liu M, Zheng S, Li H, Budowle B, Wang L, Lou Z, Ge J. High resolution tissue and cell type identification via single cell transcriptomic profiling. PLoS One 2025; 20:e0318151. [PMID: 40138334 PMCID: PMC11940611 DOI: 10.1371/journal.pone.0318151] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2024] [Accepted: 01/11/2025] [Indexed: 03/29/2025] Open
Abstract
Tissue identification can be instrumental in reconstructing a crime scene but remains a challenging task in forensic investigations. Conventionally, identifying the presence of certain tissue from tissue mixture by predefined cell type markers in bulk fashion is challenging due to limitations in sensitivity and accuracy. In contrast, single-cell RNA sequencing (scRNA-Seq) is a promising technology that has the potential to enhance or even revolutionize tissue and cell type identification. In this study, we developed a high sensitive general purpose single cell annotation pipeline, scTissueID, to accurately evaluate the single cell profile quality and precisely determine the cell and tissue types based on scRNA profiles. By incorporating a crucial and unique reference cell quality differentiation phase of targeting only high confident cells as reference, scTissueID achieved better and consistent performance in determining cell and tissue types compared to 8 state-of-art single cell annotation pipelines and 6 widely adopted machine learning algorithms, as demonstrated through a large-scale and comprehensive comparison study using both forensic-relevant and Human Cell Atlas (HCA) data. We highlighted the significance of cell quality differentiation, a previously undervalued factor. Thus, this study offers a tool capable of accurately and efficiently identifying cell and tissue types, with broad applicability to forensic investigations and other biomedical research endeavors.
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Affiliation(s)
- Muyi Liu
- Center for Human Identification, University of North Texas Health Science Center, Fort Worth, Texas, United States of America
- Department of Cell Biology, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Suilan Zheng
- Department of Chemistry, Purdue University, West Lafayette, Indiana, United States of America
| | - Hongmin Li
- Department of Computer Science, California State University, East Bay, Hayward, California, United States of America
| | - Bruce Budowle
- Department of Forensic Medicine, University of Helsinki, Finland
| | - Le Wang
- Department of Electronic and Information Engineering, North China University of Technology, Beijing, China
| | - Zhaohuan Lou
- School of Pharmaceutical Sciences, Zhejiang Chinese Medical University, Hangzhou, China
| | - Jianye Ge
- Center for Human Identification, University of North Texas Health Science Center, Fort Worth, Texas, United States of America
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8
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Shen Y, Jiang K, Tan D, Zhu M, Qiu Y, Huang P, Zou W, Deng J, Wang Z, Xiong Y, Hong D. uN2CpolyG-mediated p65 nuclear sequestration suppresses the NF-κB-NLRP3 pathway in neuronal intranuclear inclusion disease. Cell Commun Signal 2025; 23:68. [PMID: 39920690 PMCID: PMC11806584 DOI: 10.1186/s12964-025-02079-1] [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: 08/20/2024] [Accepted: 02/01/2025] [Indexed: 02/09/2025] Open
Abstract
BACKGROUND Neuronal intranuclear inclusion disease (NIID) is genetically linked to CGG repeat expansion in the 5'-untranslated region of the NOTCH2NLC gene, with nascent polyglycine-containing protein (uN2CpolyG) identified as a primary pathogenic factor. Emerging clinical evidence suggests that inflammation contributes to NIID pathogenesis, yet the underlying molecular mechanisms remain elusive. This study aimed to elucidate the molecular interaction between uN2CpolyG and the NF-κB-NLRP3 pathway. METHODS Single-cell RNA sequencing was conducted on the skin tissues of NIID patients to assess changes in the expression of genes involved in inflammatory pathways. Cell models (HEK-293T and U87-MG) transfected with CGG9/69/100 expansion vectors were used to investigate alterations in the NF-κB-NLRP3-autophagy pathway. Additionally, the therapeutic potential of NF-κB activators was evaluated in a Drosophila model with a CGG expansion knock-in. RESULTS Single-cell sequencing revealed a significant reduction in the expression of NFKBIA, encoding NF-κB inhibitor alpha (IkBa), which facilitates the nuclear translocation of p65, a key NF-κB component. uN2CpolyG directly interacted with and sequestered p65 in nuclear inclusions, leading to reduced phosphorylated p65 (p-p65) levels. This sequestration significantly downregulated the NF-κB-NLRP3 pathway, impairing autophagy, as indicated by decreased LC3II/LC3I ratios. Treatment of CGG100 cells with lipopolysaccharide (LPS) significantly increased p-p65, NLRP3, and LC3II/LC3I levels while reducing insoluble uN2CpolyG levels and intranuclear inclusions. In the Drosophila knock-in model, LPS significantly reduced the number of intranuclear inclusions and improved phenotypic manifestations. CONCLUSIONS This study revealed that uN2CpolyG directly interacts with and sequesters p65, thereby inhibiting the NF-κB-NLRP3 pathway and impairing autophagy. This mechanism highlights a novel therapeutic target for NIID and provides potentially broader insights into similar mechanisms in other neurodegenerative diseases characterized by misfolded protein aggregates.
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Affiliation(s)
- Yu Shen
- Department of Neurology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Yong Wai Zheng Street 17#, Nanchang, 330006, China
| | - Kaiyan Jiang
- Department of Neurology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Yong Wai Zheng Street 17#, Nanchang, 330006, China
| | - Dandan Tan
- Department of Neurology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Yong Wai Zheng Street 17#, Nanchang, 330006, China
- Institute of Neurology, The First Affiliated Hospital, Jiangxi Medical College, Jiangxi Academy of Clinical Medical Science, Nanchang University, Nanchang, China
- Rare Disease Center, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China
| | - Min Zhu
- Department of Neurology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Yong Wai Zheng Street 17#, Nanchang, 330006, China
- Institute of Neurology, The First Affiliated Hospital, Jiangxi Medical College, Jiangxi Academy of Clinical Medical Science, Nanchang University, Nanchang, China
- Rare Disease Center, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China
| | - Yusen Qiu
- Department of Neurology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Yong Wai Zheng Street 17#, Nanchang, 330006, China
- Institute of Neurology, The First Affiliated Hospital, Jiangxi Medical College, Jiangxi Academy of Clinical Medical Science, Nanchang University, Nanchang, China
- Rare Disease Center, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China
| | - Pencheng Huang
- Department of Neurology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Yong Wai Zheng Street 17#, Nanchang, 330006, China
- Institute of Neurology, The First Affiliated Hospital, Jiangxi Medical College, Jiangxi Academy of Clinical Medical Science, Nanchang University, Nanchang, China
- Key Laboratory of Rare Neurological Diseases of Jiangxi Provincial Health Commission, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Wenquan Zou
- Department of Neurology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Yong Wai Zheng Street 17#, Nanchang, 330006, China
- Institute of Neurology, The First Affiliated Hospital, Jiangxi Medical College, Jiangxi Academy of Clinical Medical Science, Nanchang University, Nanchang, China
| | - Jianwen Deng
- Department of Neurology, Peking University First Hospital, Beijing, China
| | - Zhaoxia Wang
- Department of Neurology, Peking University First Hospital, Beijing, China
| | - Ying Xiong
- Department of Neurology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Yong Wai Zheng Street 17#, Nanchang, 330006, China.
- Institute of Neurology, The First Affiliated Hospital, Jiangxi Medical College, Jiangxi Academy of Clinical Medical Science, Nanchang University, Nanchang, China.
- Key Laboratory of Rare Neurological Diseases of Jiangxi Provincial Health Commission, The First Affiliated Hospital of Nanchang University, Nanchang, China.
| | - Daojun Hong
- Department of Neurology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Yong Wai Zheng Street 17#, Nanchang, 330006, China.
- Institute of Neurology, The First Affiliated Hospital, Jiangxi Medical College, Jiangxi Academy of Clinical Medical Science, Nanchang University, Nanchang, China.
- Rare Disease Center, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
- Key Laboratory of Rare Neurological Diseases of Jiangxi Provincial Health Commission, The First Affiliated Hospital of Nanchang University, Nanchang, China.
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9
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Park CJ, Oh JE, Lin P, Zhou S, Bunnell M, Bikorimana E, Spinella MJ, Lim HJ, Ko CJ. A Dynamic Shift in Estrogen Receptor Expression During Granulosa Cell Differentiation in the Ovary. Endocrinology 2025; 166:bqaf006. [PMID: 39834231 PMCID: PMC12054734 DOI: 10.1210/endocr/bqaf006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/06/2024] [Revised: 12/29/2024] [Accepted: 01/18/2025] [Indexed: 01/22/2025]
Abstract
This study uncovers a dynamic shift in estrogen receptor expression during granulosa cell (GC) differentiation in the ovary, highlighting a transition from estrogen receptor alpha (ESR1) to estrogen receptor beta (ESR2). Using a transgenic mouse model with Esr1-iCre-mediated Esr2 deletion, we demonstrate that ESR2 expression is absent in GCs derived from ESR1-expressing ovarian surface epithelium (OSE) cells. Single-cell analysis of the OSE-GC lineage reveals a developmental trajectory from Esr1-expressing OSE cells to Foxl2-expressing pre-GCs, culminating in GCs exclusively expressing Esr2. Transcriptome analyses identified vasculature-derived TGFβ1 ligands as key regulators of this transition. Supporting this, TGFβ1 treatment of cultured embryonic ovaries reduced Esr1 expression while promoting Esr2 expression. This study underscores the capability of GCs to switch from ESR1 to ESR2 expression as a fundamental aspect of normal differentiation.
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Affiliation(s)
- Chan Jin Park
- Department of Comparative Biosciences, College of Veterinary Medicine, University of Illinois at Urbana-Champaign, Urbana, IL 61802, USA
- Epivara, Inc., Research Park, Champaign, IL 61820, USA
| | - Ji-Eun Oh
- Department of Comparative Biosciences, College of Veterinary Medicine, University of Illinois at Urbana-Champaign, Urbana, IL 61802, USA
| | - PoChing Lin
- Department of Comparative Biosciences, College of Veterinary Medicine, University of Illinois at Urbana-Champaign, Urbana, IL 61802, USA
| | - Sherry Zhou
- Epivara, Inc., Research Park, Champaign, IL 61820, USA
| | - Mary Bunnell
- Department of Comparative Biosciences, College of Veterinary Medicine, University of Illinois at Urbana-Champaign, Urbana, IL 61802, USA
| | - Emmanuel Bikorimana
- Department of Comparative Biosciences, College of Veterinary Medicine, University of Illinois at Urbana-Champaign, Urbana, IL 61802, USA
| | - Michael J Spinella
- Department of Comparative Biosciences, College of Veterinary Medicine, University of Illinois at Urbana-Champaign, Urbana, IL 61802, USA
| | - Hyunjung Jade Lim
- Department of Veterinary Medicine, Konkuk University, Gwangjin-gu, Seoul 05029, Korea
| | - CheMyong J Ko
- Department of Comparative Biosciences, College of Veterinary Medicine, University of Illinois at Urbana-Champaign, Urbana, IL 61802, USA
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10
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Song D, Chen S, Lee C, Li K, Ge X, Li JJ. Synthetic control removes spurious discoveries from double dipping in single-cell and spatial transcriptomics data analyses. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.07.21.550107. [PMID: 37546812 PMCID: PMC10401959 DOI: 10.1101/2023.07.21.550107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
Double dipping is a well-known pitfall in single-cell and spatial transcriptomics data analysis: after a clustering algorithm finds clusters as putative cell types or spatial domains, statistical tests are applied to the same data to identify differentially expressed (DE) genes as potential cell-type or spatial-domain markers. Because the genes that contribute to clustering are inherently likely to be identified as DE genes, double dipping can result in false-positive cell-type or spatial-domain markers, especially when clusters are spurious, leading to ambiguously defined cell types or spatial domains. To address this challenge, we propose ClusterDE, a statistical method designed to identify post-clustering DE genes as reliable markers of cell types and spatial domains, while controlling the false discovery rate (FDR) regardless of clustering quality. The core of ClusterDE involves generating synthetic null data as an in silico negative control that contains only one cell type or spatial domain, allowing for the detection and removal of spurious discoveries caused by double dipping. We demonstrate that ClusterDE controls the FDR and identifies canonical cell-type and spatial-domain markers as top DE genes, distinguishing them from housekeeping genes. ClusterDE's ability to discover reliable markers, or the absence of such markers, can be used to determine whether two ambiguous clusters should be merged. Additionally, ClusterDE is compatible with state-of-the-art analysis pipelines like Seurat and Scanpy.
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Affiliation(s)
- Dongyuan Song
- Department of Genetics and Genome Sciences, University of Connecticut Health Center, Farmington, CT 06030
- Interdepartmental Program of Bioinformatics, University of California, Los Angeles, CA 90095-7246
| | - Siqi Chen
- Department of Statistics and Data Science, University of California, Los Angeles, CA 90095-1554
| | - Christy Lee
- Department of Statistics and Data Science, University of California, Los Angeles, CA 90095-1554
| | - Kexin Li
- Department of Statistics and Data Science, University of California, Los Angeles, CA 90095-1554
| | - Xinzhou Ge
- Department of Statistics and Data Science, University of California, Los Angeles, CA 90095-1554
- Department of Statistics, Oregon State University, Corvallis, OR 97331-4606
| | - Jingyi Jessica Li
- Interdepartmental Program of Bioinformatics, University of California, Los Angeles, CA 90095-7246
- Department of Statistics and Data Science, University of California, Los Angeles, CA 90095-1554
- Department of Human Genetics, University of California, Los Angeles, CA 90095-7088
- Department of Computational Medicine, University of California, Los Angeles, CA 90095-1766
- Department of Biostatistics, University of California, Los Angeles, CA 90095-1772
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11
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Yang Y, Zhao A, Wang T, Tang Q, Qi S, Shi X, Wang F, Gao Y. Identification of driving genes of recurrent miscarriage based on transcriptome sequencing and immunoinfiltration analysis. Int Immunopharmacol 2024; 143:113095. [PMID: 39395380 DOI: 10.1016/j.intimp.2024.113095] [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: 04/15/2024] [Revised: 09/01/2024] [Accepted: 09/03/2024] [Indexed: 10/14/2024]
Abstract
AIMS Recurrent miscarriage (RM) plagues 1 %-5 % women of childbearing age. Facing the limitations of clinical treatment, its pathological mechanism remains to be clarified. METHODS Decidual tissues of three induced abortions and three RM were collected for transcriptome sequencing. The pathological features of RM were identified by differential expression genes (DEGs) analysis, GSEA, GO and KEGG analysis, and a protein-protein interaction network was constructed for DEGs, and six algorithms were used to identify hub genes. In addition, the immune characteristics of RM patients were identified by CIBERSORT, and the correlation between them and hub genes was analyzed. Furthermore, in single-cell level, different cells were grouped according to the expression level of hub genes, and the expression ratio and abundance of hub genes in different cells and their regulation on cell function were explored. RESULTS Transcriptome sequencing of patients with RM showed that a large number of genes were down-regulated, which was related to fibroblast proliferation, epithelial cell migration, female pregnancy and cell chemotaxis. Fifteen hub genes were identified by constructing a protein-protein interaction network, among which DUSP1, NR4A1 and THBS1 were involved in cell migration and chemotaxis. Immune cell infiltration analysis showed that the infiltration of T cells, macrophages and NK cells was abnormal, and there was a significant correlation with hub genes. Moreover, we found that compared with the expression of DUSP1, the non-expression of DUSP1 will reduce the extracellular matrix formation of fibroblasts and the chemotaxis of macrophages. At the same time, it is worth noting that the expression ratio and abundance of hub genes are decreased in epithelial cells, fibroblasts, macrophages and NK cells. Furthermore, single-cell analysis and in vitro and in vivo experiments show that DUSP1 and NR4A1 are low-expressed in different cells of RM patients, which is accompanied by the inhibition of fibroblast proliferation and macrophage chemotaxis. Drug prediction and screening based on hub genes show that Cinobufagin and calmidazolium are expected to be candidate drugs for RM. CONCLUSION Hub genes such as DUSP1, NR4A1 and THBS1 participate in RM by regulating epithelial cell migration, fibroblast proliferation and macrophage chemotaxis, which will provide new insight for the diagnosis and targeted therapy of RM.
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Affiliation(s)
- Yijun Yang
- The Affiliated Huaian No. 1 People's Hospital of Nanjing Medical University, China
| | - Ai Zhao
- The Affiliated Huaian No. 1 People's Hospital of Nanjing Medical University, China
| | - Ting Wang
- The Affiliated Huaian No. 1 People's Hospital of Nanjing Medical University, China
| | - Qi Tang
- The Affiliated Huaian No. 1 People's Hospital of Nanjing Medical University, China
| | - Suwan Qi
- Affiliated Women's Hospital of Jiangnan University, China
| | - Xiaoling Shi
- The Affiliated Huaian No. 1 People's Hospital of Nanjing Medical University, China
| | - Fei Wang
- The Affiliated Huaian No. 1 People's Hospital of Nanjing Medical University, China.
| | - Yingchun Gao
- The Affiliated Huaian No. 1 People's Hospital of Nanjing Medical University, China.
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12
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Ma J, Chu TK, Polo-Prieto M, Park YH, Li Y, Chen R, Mardon G, Frankfort BJ, Tran NM. Sample multiplexing for retinal single-cell RNA sequencing. iScience 2024; 27:111250. [PMID: 39569377 PMCID: PMC11576387 DOI: 10.1016/j.isci.2024.111250] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2024] [Revised: 08/09/2024] [Accepted: 10/22/2024] [Indexed: 11/22/2024] Open
Abstract
Rare cell populations can be challenging to characterize using microfluidic single-cell RNA sequencing (scRNA-seq) platforms. Typically, the population of interest must be enriched and pooled from multiple biological specimens for efficient collection. However, these practices preclude the resolution of sample origin together with phenotypic data and are problematic in experiments in which biological or technical variation is expected to be high (e.g., disease models, genetic perturbation screens, or human samples). One solution is sample multiplexing whereby each sample is tagged with a unique sequence barcode that is resolved bioinformatically. We have established a scRNA-seq sample multiplexing pipeline for mouse retinal ganglion cells using cholesterol-modified oligos. We utilized the enhanced precision of this dataset to investigate cell type distribution and transcriptomic variance across retinal samples. Additionally, we demonstrate that our multiplexed dataset can be useful for the identification of multiplets in non-labeled samples, a common challenge in scRNA-seq analysis.
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Affiliation(s)
- Justin Ma
- Department of Pathology and Immunology, Baylor College of Medicine, Houston, TX, USA
| | - Ting-Kuan Chu
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Maria Polo-Prieto
- Department of Ophthalmology, Baylor College of Medicine, Houston, TX, USA
| | - Yong H. Park
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
| | - Yumei Li
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Rui Chen
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Graeme Mardon
- Department of Pathology and Immunology, Baylor College of Medicine, Houston, TX, USA
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
- Department of Ophthalmology, Baylor College of Medicine, Houston, TX, USA
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
| | - Benjamin J. Frankfort
- Department of Ophthalmology, Baylor College of Medicine, Houston, TX, USA
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
| | - Nicholas M. Tran
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
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13
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Vasileva E, Arata C, Luo Y, Burgos R, Crump JG, Amatruda JF. Origin of Ewing sarcoma by embryonic reprogramming of neural crest to mesoderm. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.10.27.620438. [PMID: 39554045 PMCID: PMC11565755 DOI: 10.1101/2024.10.27.620438] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/19/2024]
Abstract
Ewing sarcoma is a malignant small round blue cell tumor of bones and soft tissues caused by chromosomal translocations that generate aberrant fusion oncogenes, most frequently EWSR1::FLI1. The cell of origin and mechanisms of EWSR1::FLI1-driven transformation have remained unresolved, largely due to lack of a representative animal model. By developing a zebrafish Ewing sarcoma model, we provide evidence for a neural crest origin of this cancer. Neural crest-derived cells uniquely tolerate expression of EWSR1::FLI1 and targeted expression of EWSR1::FLI1 in these cells generates Ewing sarcomas. Single-cell analysis of tumor initiation shows that EWSR1::FLI1 reprograms neural crest-derived cells to a mesoderm-like state, strikingly resulting in ectopic fins throughout the body. By profiling chromatin accessibility and genome-wide EWSR1::FLI1 binding, we find that the fusion oncogene hijacks developmental enhancers for neural crest to mesoderm reprogramming during cancer initiation. These findings show how a single mutation profoundly alters embryonic cell fate decisions to initiate a devastating childhood cancer.
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Affiliation(s)
- Elena Vasileva
- Cancer and Blood Disease Institute, Children’s Hospital Los Angeles, Los Angeles, CA 90027 USA
| | - Claire Arata
- Eli and Edythe Broad CIRM Center for Regenerative Medicine and Stem Cell Research, Department of Stem Cell Biology and Regenerative Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Yongfeng Luo
- Cancer and Blood Disease Institute, Children’s Hospital Los Angeles, Los Angeles, CA 90027 USA
| | - Ruben Burgos
- Cancer and Blood Disease Institute, Children’s Hospital Los Angeles, Los Angeles, CA 90027 USA
| | - J. Gage Crump
- Eli and Edythe Broad CIRM Center for Regenerative Medicine and Stem Cell Research, Department of Stem Cell Biology and Regenerative Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - James F. Amatruda
- Cancer and Blood Disease Institute, Children’s Hospital Los Angeles, Los Angeles, CA 90027 USA
- Departments of Pediatrics and Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
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14
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Yang X, Zhao Y, Liu W, Gao Z, Wang C, Wang C, Li S, Zhang X. Single-cell transcriptomics reveals neural stem cell trans-differentiation and cell subpopulations in whole heart decellularized extracellular matrix. BIOPHYSICS REPORTS 2024; 10:241-253. [PMID: 39281200 PMCID: PMC11399890 DOI: 10.52601/bpr.2024.240011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2024] [Accepted: 04/16/2024] [Indexed: 09/18/2024] Open
Abstract
The whole heart decellularized extracellular matrix (ECM) has become a promising scaffold material for cardiac tissue engineering. Our previous research has shown that the whole heart acellular matrix possesses the memory function regulating neural stem cells (NSCs) trans-differentiating to cardiac lineage cells. However, the cell subpopulations and phenotypes in the trans-differentiation of NSCs have not been clearly identified. Here, we performed single-cell RNA sequencing and identified 2,765 cells in the recellularized heart with NSCs revealing the cellular diversity of cardiac and neural lineage, confirming NSCs were capable of trans-differentiating into the cardiac lineage while maintaining the original ability to differentiate into the neural lineage. Notably, the trans-differentiated heart-like cells have dual signatures of neuroectoderm and cardiac mesoderm. This study unveils an in-depth mechanism underlying the trans-differentiation of NSCs and provides a new opportunity and theoretical basis for cardiac regeneration.
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Affiliation(s)
- Xiaoning Yang
- Beijing Institute of Basic Medical Sciences, Beijing 100850, China
| | - Yuwei Zhao
- Beijing Institute of Basic Medical Sciences, Beijing 100850, China
| | - Wei Liu
- Beijing Institute of Basic Medical Sciences, Beijing 100850, China
| | - Zhongbao Gao
- Beijing Institute of Basic Medical Sciences, Beijing 100850, China
| | - Chunlan Wang
- Beijing Institute of Basic Medical Sciences, Beijing 100850, China
| | - Changyong Wang
- Beijing Institute of Basic Medical Sciences, Beijing 100850, China
| | - Siwei Li
- Beijing Institute of Basic Medical Sciences, Beijing 100850, China
| | - Xiao Zhang
- Beijing Institute of Basic Medical Sciences, Beijing 100850, China
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15
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Wen Z, Ablimit A. Aquaporin 1 aggravates lipopolysaccharide-induced macrophage polarization and pyroptosis. Sci Rep 2024; 14:18569. [PMID: 39127771 PMCID: PMC11316789 DOI: 10.1038/s41598-024-68899-2] [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: 01/08/2024] [Accepted: 07/29/2024] [Indexed: 08/12/2024] Open
Abstract
Acute respiratory infections (ARIs) are associated with high mortality and morbidity. Acute lung injury (ALI) is caused by the activation of immune cells during ARIs caused by viruses such as SARS-CoV-2. Aquaporin 1 (AQP1) is distributed in a variety of immune cells and is related to the occurrence of ALI, but the mechanism is not clear. A reference map of human single cells was used to identify macrophages in COVID-19 patients at the single-cell level. "FindMarkers" was used to analyze differentially expressed genes (DEGs), and "clusterProfiler" was used to analyze the functions of the DEGs. An M1 macrophage polarization model was established with lipopolysaccharide (LPS) in vitro, and the relationships among AQP1, pyroptosis and M1 polarization were examined by using an AQP1 inhibitor. Transcriptome sequencing and RT-qPCR were used to examine the molecular mechanism by which AQP1 regulates macrophage polarization and pyroptosis. Antigen presentation, M1 polarization, migration and phagocytosis are abnormal in SARS-CoV-2-infected macrophages, which is related to the high expression of AQP1. An M1 polarization model of macrophages was constructed in vitro, and an AQP1 inhibitor was used to examine whether AQP1 could promote M1 polarization and pyroptosis in response to LPS. Transcriptome and cell experiments showed that this effect was related to a decrease in chemokines caused by AQP1 deficiency. AQP1 participates in M1 polarization and pyroptosis in macrophages by increasing the levels of chemokines induced by LPS, which provides new insights for the diagnosis and treatment of ALI.
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Affiliation(s)
- Zhuman Wen
- Department of Histology and Embryology, Basic Medical College, Xinjiang Medical University, Urumqi, China
| | - Abduxukur Ablimit
- Department of Histology and Embryology, Basic Medical College, Xinjiang Medical University, Urumqi, China.
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16
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Fu X, Guo X, Xu H, Li Y, Jin B, Zhang X, Shu C, Fan Y, Yu Y, Tian Y, Tian J, Shu J. Varied cellular abnormalities in thin vs. normal endometrium in recurrent implantation failure by single-cell transcriptomics. Reprod Biol Endocrinol 2024; 22:90. [PMID: 39085925 PMCID: PMC11293141 DOI: 10.1186/s12958-024-01263-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Accepted: 07/22/2024] [Indexed: 08/02/2024] Open
Abstract
BACKGROUND Reduced endometrium thickness and receptivity are two important reasons for recurrent implantation failure (RIF). In order to elucidate differences between these two types of endometrial defects in terms of molecular signatures, cellular interactions, and structural changes, we systematically investigated the single-cell transcriptomic atlas across three distinct groups: RIF patients with thin endometrium (≤ 6 mm, TE-RIF), RIF patients with normal endometrium thickness (≥ 8 mm, NE-RIF), and fertile individuals (Control). METHODS The late proliferative and mid-secretory phases of the endometrium were collected from three individuals in the TE-RIF group, two in the NE-RIF group, and three in the control group. The study employed a combination of advanced techniques. Single-cell RNA sequencing (scRNA-seq) was utilized to capture comprehensive transcriptomic profiles at the single-cell level, providing insights into gene expression patterns within specific cell types. Scanning and transmission electron microscopy were employed to visualize ultrastructural details of the endometrial tissue, while hematoxylin and eosin staining facilitated the examination of tissue morphology and cellular composition. Immunohistochemistry techniques were also applied to detect and localize specific protein markers relevant to endometrial receptivity and function. RESULTS Through comparative analysis of differentially expressed genes among these groups and KEGG pathway analysis, the TE-RIF group exhibited notable dysregulations in the TNF and MAPK signaling pathways, which are pivotal in stromal cell growth and endometrial receptivity. Conversely, in the NE-RIF group, disturbances in energy metabolism emerged as a primary contributor to reduced endometrial receptivity. Additionally, using CellPhoneDB for intercellular communication analysis revealed aberrant interactions between epithelial and stromal cells, impacting endometrial receptivity specifically in the TE-RIF group. CONCLUSION Overall, our findings provide valuable insights into the heterogeneous molecular pathways and cellular interactions associated with RIF in different endometrial conditions. These insights may pave the way for targeted therapeutic interventions aimed at improving endometrial receptivity and enhancing reproductive outcomes in patients undergoing ART. Further research is warranted to validate these findings and translate them into clinical applications for personalized fertility treatments. TRIAL REGISTRATION Not applicable.
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Affiliation(s)
- Xiaoying Fu
- Center for Reproductive Medicine, Department of Reproductive Endocrinology, Affiliated People's Hospital, Zhejiang Provincial People's Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Xiaoyan Guo
- Center for Reproductive Medicine, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Han Xu
- Center for Reproductive Medicine, Department of Reproductive Endocrinology, Affiliated People's Hospital, Zhejiang Provincial People's Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Yini Li
- Zhejiang Provincial Key Laboratory of Pancreatic Disease, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Bihui Jin
- Center for Reproductive Medicine, Department of Reproductive Endocrinology, Affiliated People's Hospital, Zhejiang Provincial People's Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Xirong Zhang
- Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Chongyi Shu
- Center for Reproductive Medicine, Department of Reproductive Endocrinology, Affiliated People's Hospital, Zhejiang Provincial People's Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Yuhang Fan
- Center for Reproductive Medicine, Department of Reproductive Endocrinology, Affiliated People's Hospital, Zhejiang Provincial People's Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Yiqi Yu
- Center for Reproductive Medicine, Department of Reproductive Endocrinology, Affiliated People's Hospital, Zhejiang Provincial People's Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Yuqing Tian
- Center for Reproductive Medicine, Department of Reproductive Endocrinology, Affiliated People's Hospital, Zhejiang Provincial People's Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Jiao Tian
- Center for Reproductive Medicine, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jing Shu
- Center for Reproductive Medicine, Department of Reproductive Endocrinology, Affiliated People's Hospital, Zhejiang Provincial People's Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, China.
- Center for Reproductive Medicine, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
- The First Affiliated Hospital, Zhejiang University School of Medicine, 79 Qingchun Road, Shangcheng District, Hangzhou, Zhejiang, China.
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17
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Dunsmore G, Guo W, Li Z, Bejarano DA, Pai R, Yang K, Kwok I, Tan L, Ng M, De La Calle Fabregat C, Yatim A, Bougouin A, Mulder K, Thomas J, Villar J, Bied M, Kloeckner B, Dutertre CA, Gessain G, Chakarov S, Liu Z, Scoazec JY, Lennon-Dumenil AM, Marichal T, Sautès-Fridman C, Fridman WH, Sharma A, Su B, Schlitzer A, Ng LG, Blériot C, Ginhoux F. Timing and location dictate monocyte fate and their transition to tumor-associated macrophages. Sci Immunol 2024; 9:eadk3981. [PMID: 39058763 DOI: 10.1126/sciimmunol.adk3981] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2023] [Accepted: 07/03/2024] [Indexed: 07/28/2024]
Abstract
Tumor-associated macrophages (TAMs) are a heterogeneous population of cells whose phenotypes and functions are shaped by factors that are incompletely understood. Herein, we asked when and where TAMs arise from blood monocytes and how they evolve during tumor development. We initiated pancreatic ductal adenocarcinoma (PDAC) in inducible monocyte fate-mapping mice and combined single-cell transcriptomics and high-dimensional flow cytometry to profile the monocyte-to-TAM transition. We revealed that monocytes differentiate first into a transient intermediate population of TAMs that generates two longer-lived lineages of terminally differentiated TAMs with distinct gene expression profiles, phenotypes, and intratumoral localization. Transcriptome datasets and tumor samples from patients with PDAC evidenced parallel TAM populations in humans and their prognostic associations. These insights will support the design of new therapeutic strategies targeting TAMs in PDAC.
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Affiliation(s)
- Garett Dunsmore
- Institut Gustave Roussy, INSERM U1015, Bâtiment de Médecine Moléculaire 114 rue Edouard Vaillant, 94800 Villejuif, France
- Université Paris-Saclay, Ile-de-France, France
| | - Wei Guo
- Shanghai Institute of Immunology, Department of Immunology and Microbiology, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Ziyi Li
- Shanghai Institute of Immunology, Department of Immunology and Microbiology, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - David Alejandro Bejarano
- Quantitative Systems Biology, Life and Medical Sciences Institute, University of Bonn, 53115 Bonn, Germany
| | - Rhea Pai
- Curtin Medical School, Curtin University, Bentley, WA, Australia
| | - Katharine Yang
- Singapore Immunology Network (SIgN), A*STAR, 8A Biomedical Grove, Immunos Building, Level 3, Singapore 138648, Singapore
| | - Immanuel Kwok
- Singapore Immunology Network (SIgN), A*STAR, 8A Biomedical Grove, Immunos Building, Level 3, Singapore 138648, Singapore
| | - Leonard Tan
- Singapore Immunology Network (SIgN), A*STAR, 8A Biomedical Grove, Immunos Building, Level 3, Singapore 138648, Singapore
| | - Melissa Ng
- Singapore Immunology Network (SIgN), A*STAR, 8A Biomedical Grove, Immunos Building, Level 3, Singapore 138648, Singapore
| | - Carlos De La Calle Fabregat
- Institut Gustave Roussy, INSERM U1015, Bâtiment de Médecine Moléculaire 114 rue Edouard Vaillant, 94800 Villejuif, France
| | - Aline Yatim
- Institut Curie, PSL University, INSERM U932, Immunity and Cancer, 75005 Paris, France
| | - Antoine Bougouin
- Centre de Recherche des Cordeliers, INSERM, Sorbonne Université, USPC Université Paris Cité, Equipe Labellisée Ligue Nationale Contre le Cancer, Paris, France
| | - Kevin Mulder
- Institut Gustave Roussy, INSERM U1015, Bâtiment de Médecine Moléculaire 114 rue Edouard Vaillant, 94800 Villejuif, France
- Université Paris-Saclay, Ile-de-France, France
| | - Jake Thomas
- Quantitative Systems Biology, Life and Medical Sciences Institute, University of Bonn, 53115 Bonn, Germany
| | - Javiera Villar
- Institut Gustave Roussy, INSERM U1015, Bâtiment de Médecine Moléculaire 114 rue Edouard Vaillant, 94800 Villejuif, France
| | - Mathilde Bied
- Institut Gustave Roussy, INSERM U1015, Bâtiment de Médecine Moléculaire 114 rue Edouard Vaillant, 94800 Villejuif, France
- Université Paris-Saclay, Ile-de-France, France
| | - Benoit Kloeckner
- Institut Gustave Roussy, INSERM U1015, Bâtiment de Médecine Moléculaire 114 rue Edouard Vaillant, 94800 Villejuif, France
- Université Paris-Saclay, Ile-de-France, France
| | - Charles-Antoine Dutertre
- Institut Gustave Roussy, INSERM U1015, Bâtiment de Médecine Moléculaire 114 rue Edouard Vaillant, 94800 Villejuif, France
| | - Grégoire Gessain
- Institut Gustave Roussy, INSERM U1015, Bâtiment de Médecine Moléculaire 114 rue Edouard Vaillant, 94800 Villejuif, France
| | - Svetoslav Chakarov
- Shanghai Institute of Immunology, Department of Immunology and Microbiology, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Zhaoyuan Liu
- Shanghai Institute of Immunology, Department of Immunology and Microbiology, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Jean-Yves Scoazec
- Institut Gustave Roussy, INSERM U1015, Bâtiment de Médecine Moléculaire 114 rue Edouard Vaillant, 94800 Villejuif, France
| | | | - Thomas Marichal
- Laboratory of Immunophysiology, GIGA Institute, Liège University, Liège, Belgium
- Faculty of Veterinary Medicine, Liège University, Liège, Belgium
- Walloon Excellence in Life Sciences and Biotechnology (WELBIO) Department, WEL Research Institute, Wavre, Belgium
| | - Catherine Sautès-Fridman
- Centre de Recherche des Cordeliers, INSERM, Sorbonne Université, USPC Université Paris Cité, Equipe Labellisée Ligue Nationale Contre le Cancer, Paris, France
| | - Wolf Herman Fridman
- Centre de Recherche des Cordeliers, INSERM, Sorbonne Université, USPC Université Paris Cité, Equipe Labellisée Ligue Nationale Contre le Cancer, Paris, France
| | - Ankur Sharma
- Curtin Medical School, Curtin University, Bentley, WA, Australia
- Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, 6 Verdun Street, Nedlands, Perth, WA 6009, Australia
- Institute of Molecular and Cellular Biology, A*STAR, Singapore 138673, Singapore
- KK Research Centre, KK Women's and Children's Hospital, Singapore 229899, Singapore
- Translational Genomics Program, Garvan Institute of Medical Research and Kinghorn Cancer Centre, Darlinghurst, NSW, Australia
| | - Bing Su
- Shanghai Institute of Immunology, Department of Immunology and Microbiology, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Andreas Schlitzer
- Quantitative Systems Biology, Life and Medical Sciences Institute, University of Bonn, 53115 Bonn, Germany
| | - Lai Guan Ng
- Shanghai Immune Therapy Institute Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200010, China
- Department of Microbiology and Immunology, National University of Singapore, Singapore, Singapore
| | - Camille Blériot
- Institut Gustave Roussy, INSERM U1015, Bâtiment de Médecine Moléculaire 114 rue Edouard Vaillant, 94800 Villejuif, France
- Institut Necker Enfants Malades (INEM), CNRS UMR 8253, INSERM U1151, 160 rue de Vaugirard, 75015 Paris, France
| | - Florent Ginhoux
- Institut Gustave Roussy, INSERM U1015, Bâtiment de Médecine Moléculaire 114 rue Edouard Vaillant, 94800 Villejuif, France
- Université Paris-Saclay, Ile-de-France, France
- Shanghai Institute of Immunology, Department of Immunology and Microbiology, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Singapore Immunology Network (SIgN), A*STAR, 8A Biomedical Grove, Immunos Building, Level 3, Singapore 138648, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228 Singapore
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18
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Fan Z, Karakone M, Nagarajan S, Nagy N, Mildenberger W, Petrova E, Hinte LC, Bijnen M, Häne P, Nelius E, Chen J, Ferapontova I, von Meyenn F, Trepiccione F, Berber M, Ribas DP, Eichmann A, Zennaro MC, Takeda N, Fischer JW, Spyroglou A, Reincke M, Beuschlein F, Loffing J, Greter M, Stockmann C. Macrophages preserve endothelial cell specialization in the adrenal gland to modulate aldosterone secretion and blood pressure. Cell Rep 2024; 43:114395. [PMID: 38941187 DOI: 10.1016/j.celrep.2024.114395] [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: 02/09/2023] [Revised: 04/22/2024] [Accepted: 06/07/2024] [Indexed: 06/30/2024] Open
Abstract
Macrophages play crucial roles in organ-specific functions and homeostasis. In the adrenal gland, macrophages closely associate with sinusoidal capillaries in the aldosterone-producing zona glomerulosa. We demonstrate that macrophages preserve capillary specialization and modulate aldosterone secretion. Using macrophage-specific deletion of VEGF-A, single-cell transcriptomics, and functional phenotyping, we found that the loss of VEGF-A depletes PLVAP+ fenestrated endothelial cells in the zona glomerulosa, leading to increased basement membrane collagen IV deposition and subendothelial fibrosis. This results in increased aldosterone secretion, called "haptosecretagogue" signaling. Human aldosterone-producing adenomas also show capillary rarefaction and basement membrane thickening. Mice with myeloid cell-specific VEGF-A deletion exhibit elevated serum aldosterone, hypokalemia, and hypertension, mimicking primary aldosteronism. These findings underscore macrophage-to-endothelial cell signaling as essential for endothelial cell specialization, adrenal gland function, and blood pressure regulation, with broader implications for other endocrine organs.
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Affiliation(s)
- Zheng Fan
- University of Zurich, Institute of Anatomy, 8057 Zurich, Switzerland.
| | - Mara Karakone
- University of Zurich, Institute of Anatomy, 8057 Zurich, Switzerland
| | | | - Nadine Nagy
- Division of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Wiebke Mildenberger
- University of Zurich, Institute for Experimental Immunology, 8057 Zurich, Switzerland
| | - Ekaterina Petrova
- University of Zurich, Institute for Experimental Immunology, 8057 Zurich, Switzerland
| | - Laura Catharina Hinte
- Laboratory of Nutrition and Metabolic Epigenetics, Institute for Food, Nutrition and Health, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Mitchell Bijnen
- University of Zurich, Institute for Experimental Immunology, 8057 Zurich, Switzerland
| | - Philipp Häne
- University of Zurich, Institute for Experimental Immunology, 8057 Zurich, Switzerland
| | - Eric Nelius
- University of Zurich, Institute of Anatomy, 8057 Zurich, Switzerland
| | - Jing Chen
- University of Zurich, Institute of Anatomy, 8057 Zurich, Switzerland
| | - Irina Ferapontova
- University of Zurich, Institute of Anatomy, 8057 Zurich, Switzerland
| | - Ferdinand von Meyenn
- Laboratory of Nutrition and Metabolic Epigenetics, Institute for Food, Nutrition and Health, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Francesco Trepiccione
- Department of Translational Medical Sciences, University of Campania Luigi Vanvitelli, Naples, Italy
| | - Mesut Berber
- University of Zurich, Institute of Anatomy, 8057 Zurich, Switzerland
| | - David Penton Ribas
- Electrophysiology Facility (e-phac), Department of Molecular Life Sciences, University of Zurich (UZH), 8057 Zürich, Switzerland
| | - Anne Eichmann
- Cardiovascular Research Center and Department of Cellular and Molecular Physiology, Yale University School of Medicine, New Haven, CT, USA
| | | | - Norihiko Takeda
- Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, Japan
| | - Jens W Fischer
- Institute of Pharmacology and Clinical Pharmacology, Medical Faculty, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany
| | - Ariadni Spyroglou
- Klinik für Endokrinologie, Diabetologie, und Klinische Ernährung, UniversitätsSpital Zürich (USZ) and UZH, Raemistrasse 100, 8091 Zurich, Switzerland; Medizinische Klinik und Poliklinik IV, Ludwig-Maximilians-University (LMU), Munich, Germany
| | - Martin Reincke
- Klinik für Endokrinologie, Diabetologie, und Klinische Ernährung, UniversitätsSpital Zürich (USZ) and UZH, Raemistrasse 100, 8091 Zurich, Switzerland
| | - Felix Beuschlein
- Klinik für Endokrinologie, Diabetologie, und Klinische Ernährung, UniversitätsSpital Zürich (USZ) and UZH, Raemistrasse 100, 8091 Zurich, Switzerland; Medizinische Klinik und Poliklinik IV, Ludwig-Maximilians-University (LMU), Munich, Germany
| | - Johannes Loffing
- University of Zurich, Institute of Anatomy, 8057 Zurich, Switzerland
| | - Melanie Greter
- University of Zurich, Institute for Experimental Immunology, 8057 Zurich, Switzerland
| | - Christian Stockmann
- University of Zurich, Institute of Anatomy, 8057 Zurich, Switzerland; INSERM U970, Paris Cardiovascular Research Center, Paris, France.
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19
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Hegde S, Giotti B, Soong BY, Halasz L, Berichel JL, Magen A, Kloeckner B, Mattiuz R, Park MD, Marks A, Belabed M, Hamon P, Chin T, Troncoso L, Lee JJ, Ahimovic D, Bale M, Chung G, D'souza D, Angeliadis K, Dawson T, Kim-Schulze S, Flores RM, Kaufman AJ, Ginhoux F, Josefowicz SZ, Ma S, Tsankov AM, Marron TU, Brown BD, Merad M. Myeloid progenitor dysregulation fuels immunosuppressive macrophages in tumors. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.24.600383. [PMID: 38979166 PMCID: PMC11230224 DOI: 10.1101/2024.06.24.600383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/10/2024]
Abstract
Monocyte-derived macrophages (mo-macs) drive immunosuppression in the tumor microenvironment (TME) and tumor-enhanced myelopoiesis in the bone marrow (BM) fuels these populations. Here, we performed paired transcriptome and chromatin analysis over the continuum of BM myeloid progenitors, circulating monocytes, and tumor-infiltrating mo-macs in mice and in patients with lung cancer to identify myeloid progenitor programs that fuel pro-tumorigenic mo-macs. Analyzing chromatin accessibility and histone mark changes, we show that lung tumors prime accessibility for Nfe2l2 (NRF2) in BM myeloid progenitors as a cytoprotective response to oxidative stress. NRF2 activity is sustained and increased during monocyte differentiation into mo-macs in the lung TME to regulate oxidative stress, in turn promoting metabolic adaptation, resistance to cell death, and contributing to immunosuppressive phenotype. NRF2 genetic deletion and pharmacological inhibition significantly reduced mo-macs' survival and immunosuppression in the TME, enabling NK and T cell therapeutic antitumor immunity and synergizing with checkpoint blockade strategies. Altogether, our study identifies a targetable epigenetic node of myeloid progenitor dysregulation that sustains immunoregulatory mo-macs in the TME.
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20
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Tian Y, Wu L, Huang CC, Wang L. Identify Regulatory eQTLs by Multiome Sequencing in Prostate Single Cells. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.19.599704. [PMID: 38948854 PMCID: PMC11213234 DOI: 10.1101/2024.06.19.599704] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Abstract
While genome-wide association studies and expression quantitative trait loci (eQTL) analysis have made significant progress in identifying noncoding variants associated with prostate cancer risk and bulk tissue transcriptome changes, the regulatory effect of these genetic elements on gene expression remains largely unknown. Recent developments in single-cell sequencing have made it possible to perform ATAC-seq and RNA-seq profiling simultaneously to capture functional associations between chromatin accessibility and gene expression. In this study, we tested our hypothesis that this multiome single-cell approach allows for mapping regulatory elements and their target genes at prostate cancer risk loci. We applied a 10X Multiome ATAC + Gene Expression platform to encapsulate Tn5 transposase-tagged nuclei from multiple prostate cell lines for a total of 65,501 high quality single cells from RWPE1, RWPE2, PrEC, BPH1, DU145, PC3, 22Rv1 and LNCaP cell lines. To address data sparsity commonly seen in the single-cell sequencing, we performed targeted sequencing to enrich sequencing data at prostate cancer risk loci involving 2,730 candidate germline variants and 273 associated genes. Although not increasing the number of captured cells, the targeted multiome data did improve eQTL gene expression abundance by about 20% and chromatin accessibility abundance by about 5%. Based on this multiomic profiling, we further associated RNA expression alterations with chromatin accessibility of germline variants at single cell levels. Cross validation analysis showed high overlaps between the multiome associations and the bulk eQTL findings from GTEx prostate cohort. We found that about 20% of GTEx eQTLs were covered within the significant multiome associations (p-value ≤ 0.05, gene abundance percentage ≥ 5%), and roughly 10% of the multiome associations could be identified by significant GTEx eQTLs. We also analyzed accessible regions with available heterozygous SNP reads and observed more frequent association in genomic regions with allelically accessible variants (p = 0.0055). Among these findings were previously reported regulatory variants including rs60464856-RUVBL1 (multiome p-value = 0.0099 in BPH1) and rs7247241-SPINT2 (multiome p-value = 0.0002- 0.0004 in 22Rv1). We also functionally validated a new regulatory SNP and its target gene rs2474694-VPS53 (multiome p-value = 0.00956 in BPH1 and 0.00625 in DU145) by reporter assay and SILAC proteomics sequencing. Taken together, our data demonstrated the feasibility of the multiome single-cell approach for identifying regulatory SNPs and their regulated genes.
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Affiliation(s)
- Yijun Tian
- Department of Tumor Biology, Moffitt Cancer Center, 12902 Magnolia Drive, Tampa, FL 33612, United States
| | - Lang Wu
- Population Sciences in the Pacific Program, University of Hawai i Cancer Center, University of Hawai i at Mānoa, Honolulu, HI 96813, USA
| | - Chang-Ching Huang
- Zilber College of Public Health, University of Wisconsin, Milwaukee, WI 53226, United States
| | - Liang Wang
- Department of Tumor Biology, Moffitt Cancer Center, 12902 Magnolia Drive, Tampa, FL 33612, United States
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21
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Li C, Shao X, Zhang S, Wang Y, Jin K, Yang P, Lu X, Fan X, Wang Y. scRank infers drug-responsive cell types from untreated scRNA-seq data using a target-perturbed gene regulatory network. Cell Rep Med 2024; 5:101568. [PMID: 38754419 PMCID: PMC11228399 DOI: 10.1016/j.xcrm.2024.101568] [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: 05/05/2023] [Revised: 12/27/2023] [Accepted: 04/21/2024] [Indexed: 05/18/2024]
Abstract
Cells respond divergently to drugs due to the heterogeneity among cell populations. Thus, it is crucial to identify drug-responsive cell populations in order to accurately elucidate the mechanism of drug action, which is still a great challenge. Here, we address this problem with scRank, which employs a target-perturbed gene regulatory network to rank drug-responsive cell populations via in silico drug perturbations using untreated single-cell transcriptomic data. We benchmark scRank on simulated and real datasets, which shows the superior performance of scRank over existing methods. When applied to medulloblastoma and major depressive disorder datasets, scRank identifies drug-responsive cell types that are consistent with the literature. Moreover, scRank accurately uncovers the macrophage subpopulation responsive to tanshinone IIA and its potential targets in myocardial infarction, with experimental validation. In conclusion, scRank enables the inference of drug-responsive cell types using untreated single-cell data, thus providing insights into the cellular-level impacts of therapeutic interventions.
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Affiliation(s)
- Chengyu Li
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China; National Key Laboratory of Chinese Medicine Modernization, Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing 314103, China
| | - Xin Shao
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China; National Key Laboratory of Chinese Medicine Modernization, Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing 314103, China.
| | - Shujing Zhang
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China; Innovation Institute for Artificial Intelligence in Medicine, Zhejiang University, Hangzhou, China
| | - Yingchao Wang
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China; Innovation Institute for Artificial Intelligence in Medicine, Zhejiang University, Hangzhou, China
| | - Kaiyu Jin
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China; National Key Laboratory of Chinese Medicine Modernization, Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing 314103, China
| | - Penghui Yang
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China; National Key Laboratory of Chinese Medicine Modernization, Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing 314103, China
| | - Xiaoyan Lu
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China; Innovation Institute for Artificial Intelligence in Medicine, Zhejiang University, Hangzhou, China
| | - Xiaohui Fan
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China; National Key Laboratory of Chinese Medicine Modernization, Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing 314103, China; Jinhua Institute of Zhejiang University, Jinhua 321299, China; Zhejiang Key Laboratory of Precision Diagnosis and Therapy for Major Gynecological Diseases, Women's Hospital, Zhejiang University School of Medicine, Hangzhou 310006, China.
| | - Yi Wang
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China; National Key Laboratory of Chinese Medicine Modernization, Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing 314103, China.
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22
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Gao Q, Ji Z, Wang L, Owzar K, Li QJ, Chan C, Xie J. SifiNet: a robust and accurate method to identify feature gene sets and annotate cells. Nucleic Acids Res 2024; 52:e46. [PMID: 38647069 PMCID: PMC11109959 DOI: 10.1093/nar/gkae307] [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: 08/10/2023] [Revised: 03/25/2024] [Accepted: 04/14/2024] [Indexed: 04/25/2024] Open
Abstract
SifiNet is a robust and accurate computational pipeline for identifying distinct gene sets, extracting and annotating cellular subpopulations, and elucidating intrinsic relationships among these subpopulations. Uniquely, SifiNet bypasses the cell clustering stage, commonly integrated into other cellular annotation pipelines, thereby circumventing potential inaccuracies in clustering that may compromise subsequent analyses. Consequently, SifiNet has demonstrated superior performance in multiple experimental datasets compared with other state-of-the-art methods. SifiNet can analyze both single-cell RNA and ATAC sequencing data, thereby rendering comprehensive multi-omic cellular profiles. It is conveniently available as an open-source R package.
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Affiliation(s)
- Qi Gao
- Department of Biostatistics and Bioinformatics, Duke University, USA
| | - Zhicheng Ji
- Department of Biostatistics and Bioinformatics, Duke University, USA
| | - Liuyang Wang
- Department of Molecular Genetics and Microbiology, Duke University, USA
| | - Kouros Owzar
- Department of Biostatistics and Bioinformatics, Duke University, USA
| | - Qi-Jing Li
- Institute of Molecular and Cell Biology, Agency for Science, Technology and Research, Singapore
- Singapore Immunology Network, Agency for Science, Technology and Research, Singapore
| | - Cliburn Chan
- Department of Biostatistics and Bioinformatics, Duke University, USA
| | - Jichun Xie
- Department of Biostatistics and Bioinformatics, Duke University, USA
- Department of Mathematics, Duke University, USA
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23
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Tamiato A, Tombor LS, Fischer A, Muhly-Reinholz M, Vanicek LR, Toğru BN, Neitz J, Glaser SF, Merten M, Rodriguez Morales D, Kwon J, Klatt S, Schumacher B, Günther S, Abplanalp WT, John D, Fleming I, Wettschureck N, Dimmeler S, Luxán G. Age-Dependent RGS5 Loss in Pericytes Induces Cardiac Dysfunction and Fibrosis. Circ Res 2024; 134:1240-1255. [PMID: 38563133 PMCID: PMC11081481 DOI: 10.1161/circresaha.123.324183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Revised: 03/11/2024] [Accepted: 03/20/2024] [Indexed: 04/04/2024]
Abstract
BACKGROUND Pericytes are capillary-associated mural cells involved in the maintenance and stability of the vascular network. Although aging is one of the main risk factors for cardiovascular disease, the consequences of aging on cardiac pericytes are unknown. METHODS In this study, we have combined single-nucleus RNA sequencing and histological analysis to determine the effects of aging on cardiac pericytes. Furthermore, we have conducted in vivo and in vitro analysis of RGS5 (regulator of G-protein signaling 5) loss of function and finally have performed pericytes-fibroblasts coculture studies to understand the effect of RGS5 deletion in pericytes on the neighboring fibroblasts. RESULTS Aging reduced the pericyte area and capillary coverage in the murine heart. Single-nucleus RNA sequencing analysis further revealed that the expression of Rgs5 was reduced in cardiac pericytes from aged mice. In vivo and in vitro studies showed that the deletion of RGS5 impaired cardiac function, induced fibrosis, and morphological changes in pericytes characterized by a profibrotic gene expression signature and the expression of different ECM (extracellular matrix) components and growth factors, for example, TGFB2 and PDGFB. Indeed, culturing fibroblasts with the supernatant of RGS5-deficient pericytes induced their activation as evidenced by the increased expression of αSMA (alpha smooth muscle actin) in a TGFβ (transforming growth factor beta)2-dependent mechanism. CONCLUSIONS Our results have identified RGS5 as a crucial regulator of pericyte function during cardiac aging. The deletion of RGS5 causes cardiac dysfunction and induces myocardial fibrosis, one of the hallmarks of cardiac aging.
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Affiliation(s)
- Anita Tamiato
- Institute of Cardiovascular Regeneration, Center of Molecular Medicine (A.T., L.S.T., A.F., M.M.-R., L.R.V., B.N.T., J.N., S.F.G., M.M., D.R.M., B.S., W.T.A., D.J., S.D., G.L.), Goethe University Frankfurt, Germany
- Cardiopulmonary Institute (A.T., L.S.T., S.F.G., M.M., S.K., B.S., S.G., W.T.A., D.J., I.F., N.W., S.D., G.L.), Goethe University Frankfurt, Germany
- German Center for Cardiovascular Research Deutsches Zentrum für Herz-Kreislauf-Forschung (DZHK), Frankfurt am Main, Germany (A.T., L.S.T., S.F.G., M.M., B.S., S.G., W.T.A., D.J., I.F., N.W., S.D., G.L.)
| | - Lukas S. Tombor
- Institute of Cardiovascular Regeneration, Center of Molecular Medicine (A.T., L.S.T., A.F., M.M.-R., L.R.V., B.N.T., J.N., S.F.G., M.M., D.R.M., B.S., W.T.A., D.J., S.D., G.L.), Goethe University Frankfurt, Germany
- Cardiopulmonary Institute (A.T., L.S.T., S.F.G., M.M., S.K., B.S., S.G., W.T.A., D.J., I.F., N.W., S.D., G.L.), Goethe University Frankfurt, Germany
- German Center for Cardiovascular Research Deutsches Zentrum für Herz-Kreislauf-Forschung (DZHK), Frankfurt am Main, Germany (A.T., L.S.T., S.F.G., M.M., B.S., S.G., W.T.A., D.J., I.F., N.W., S.D., G.L.)
| | - Ariane Fischer
- Institute of Cardiovascular Regeneration, Center of Molecular Medicine (A.T., L.S.T., A.F., M.M.-R., L.R.V., B.N.T., J.N., S.F.G., M.M., D.R.M., B.S., W.T.A., D.J., S.D., G.L.), Goethe University Frankfurt, Germany
| | - Marion Muhly-Reinholz
- Institute of Cardiovascular Regeneration, Center of Molecular Medicine (A.T., L.S.T., A.F., M.M.-R., L.R.V., B.N.T., J.N., S.F.G., M.M., D.R.M., B.S., W.T.A., D.J., S.D., G.L.), Goethe University Frankfurt, Germany
| | - Leah Rebecca Vanicek
- Institute of Cardiovascular Regeneration, Center of Molecular Medicine (A.T., L.S.T., A.F., M.M.-R., L.R.V., B.N.T., J.N., S.F.G., M.M., D.R.M., B.S., W.T.A., D.J., S.D., G.L.), Goethe University Frankfurt, Germany
| | - Büşra Nur Toğru
- Institute of Cardiovascular Regeneration, Center of Molecular Medicine (A.T., L.S.T., A.F., M.M.-R., L.R.V., B.N.T., J.N., S.F.G., M.M., D.R.M., B.S., W.T.A., D.J., S.D., G.L.), Goethe University Frankfurt, Germany
| | - Jessica Neitz
- Institute of Cardiovascular Regeneration, Center of Molecular Medicine (A.T., L.S.T., A.F., M.M.-R., L.R.V., B.N.T., J.N., S.F.G., M.M., D.R.M., B.S., W.T.A., D.J., S.D., G.L.), Goethe University Frankfurt, Germany
| | - Simone Franziska Glaser
- Institute of Cardiovascular Regeneration, Center of Molecular Medicine (A.T., L.S.T., A.F., M.M.-R., L.R.V., B.N.T., J.N., S.F.G., M.M., D.R.M., B.S., W.T.A., D.J., S.D., G.L.), Goethe University Frankfurt, Germany
- German Center for Cardiovascular Research Deutsches Zentrum für Herz-Kreislauf-Forschung (DZHK), Frankfurt am Main, Germany (A.T., L.S.T., S.F.G., M.M., B.S., S.G., W.T.A., D.J., I.F., N.W., S.D., G.L.)
| | - Maximilian Merten
- Institute of Cardiovascular Regeneration, Center of Molecular Medicine (A.T., L.S.T., A.F., M.M.-R., L.R.V., B.N.T., J.N., S.F.G., M.M., D.R.M., B.S., W.T.A., D.J., S.D., G.L.), Goethe University Frankfurt, Germany
- Cardiopulmonary Institute (A.T., L.S.T., S.F.G., M.M., S.K., B.S., S.G., W.T.A., D.J., I.F., N.W., S.D., G.L.), Goethe University Frankfurt, Germany
- German Center for Cardiovascular Research Deutsches Zentrum für Herz-Kreislauf-Forschung (DZHK), Frankfurt am Main, Germany (A.T., L.S.T., S.F.G., M.M., B.S., S.G., W.T.A., D.J., I.F., N.W., S.D., G.L.)
| | - David Rodriguez Morales
- Institute of Cardiovascular Regeneration, Center of Molecular Medicine (A.T., L.S.T., A.F., M.M.-R., L.R.V., B.N.T., J.N., S.F.G., M.M., D.R.M., B.S., W.T.A., D.J., S.D., G.L.), Goethe University Frankfurt, Germany
| | - Jeonghyeon Kwon
- Department of Pharmacology (J.K., N.W.), Max Planck Institute for Heart and Lung Research, Bad Nauheim, Germany
| | - Stephan Klatt
- Cardiopulmonary Institute (A.T., L.S.T., S.F.G., M.M., S.K., B.S., S.G., W.T.A., D.J., I.F., N.W., S.D., G.L.), Goethe University Frankfurt, Germany
- Institute for Vascular Signalling, Center of Molecular Medicine (S.K., I.F.), Goethe University Frankfurt, Germany
| | - Bianca Schumacher
- Institute of Cardiovascular Regeneration, Center of Molecular Medicine (A.T., L.S.T., A.F., M.M.-R., L.R.V., B.N.T., J.N., S.F.G., M.M., D.R.M., B.S., W.T.A., D.J., S.D., G.L.), Goethe University Frankfurt, Germany
- Cardiopulmonary Institute (A.T., L.S.T., S.F.G., M.M., S.K., B.S., S.G., W.T.A., D.J., I.F., N.W., S.D., G.L.), Goethe University Frankfurt, Germany
- German Center for Cardiovascular Research Deutsches Zentrum für Herz-Kreislauf-Forschung (DZHK), Frankfurt am Main, Germany (A.T., L.S.T., S.F.G., M.M., B.S., S.G., W.T.A., D.J., I.F., N.W., S.D., G.L.)
| | - Stefan Günther
- Cardiopulmonary Institute (A.T., L.S.T., S.F.G., M.M., S.K., B.S., S.G., W.T.A., D.J., I.F., N.W., S.D., G.L.), Goethe University Frankfurt, Germany
- German Center for Cardiovascular Research Deutsches Zentrum für Herz-Kreislauf-Forschung (DZHK), Frankfurt am Main, Germany (A.T., L.S.T., S.F.G., M.M., B.S., S.G., W.T.A., D.J., I.F., N.W., S.D., G.L.)
- Bioinformatics and Deep Sequencing Platform (S.G.), Max Planck Institute for Heart and Lung Research, Bad Nauheim, Germany
| | - Wesley T. Abplanalp
- Institute of Cardiovascular Regeneration, Center of Molecular Medicine (A.T., L.S.T., A.F., M.M.-R., L.R.V., B.N.T., J.N., S.F.G., M.M., D.R.M., B.S., W.T.A., D.J., S.D., G.L.), Goethe University Frankfurt, Germany
- Cardiopulmonary Institute (A.T., L.S.T., S.F.G., M.M., S.K., B.S., S.G., W.T.A., D.J., I.F., N.W., S.D., G.L.), Goethe University Frankfurt, Germany
- German Center for Cardiovascular Research Deutsches Zentrum für Herz-Kreislauf-Forschung (DZHK), Frankfurt am Main, Germany (A.T., L.S.T., S.F.G., M.M., B.S., S.G., W.T.A., D.J., I.F., N.W., S.D., G.L.)
| | - David John
- Institute of Cardiovascular Regeneration, Center of Molecular Medicine (A.T., L.S.T., A.F., M.M.-R., L.R.V., B.N.T., J.N., S.F.G., M.M., D.R.M., B.S., W.T.A., D.J., S.D., G.L.), Goethe University Frankfurt, Germany
- Cardiopulmonary Institute (A.T., L.S.T., S.F.G., M.M., S.K., B.S., S.G., W.T.A., D.J., I.F., N.W., S.D., G.L.), Goethe University Frankfurt, Germany
- German Center for Cardiovascular Research Deutsches Zentrum für Herz-Kreislauf-Forschung (DZHK), Frankfurt am Main, Germany (A.T., L.S.T., S.F.G., M.M., B.S., S.G., W.T.A., D.J., I.F., N.W., S.D., G.L.)
| | - Ingrid Fleming
- Cardiopulmonary Institute (A.T., L.S.T., S.F.G., M.M., S.K., B.S., S.G., W.T.A., D.J., I.F., N.W., S.D., G.L.), Goethe University Frankfurt, Germany
- Institute for Vascular Signalling, Center of Molecular Medicine (S.K., I.F.), Goethe University Frankfurt, Germany
- German Center for Cardiovascular Research Deutsches Zentrum für Herz-Kreislauf-Forschung (DZHK), Frankfurt am Main, Germany (A.T., L.S.T., S.F.G., M.M., B.S., S.G., W.T.A., D.J., I.F., N.W., S.D., G.L.)
| | - Nina Wettschureck
- Cardiopulmonary Institute (A.T., L.S.T., S.F.G., M.M., S.K., B.S., S.G., W.T.A., D.J., I.F., N.W., S.D., G.L.), Goethe University Frankfurt, Germany
- German Center for Cardiovascular Research Deutsches Zentrum für Herz-Kreislauf-Forschung (DZHK), Frankfurt am Main, Germany (A.T., L.S.T., S.F.G., M.M., B.S., S.G., W.T.A., D.J., I.F., N.W., S.D., G.L.)
- Department of Pharmacology (J.K., N.W.), Max Planck Institute for Heart and Lung Research, Bad Nauheim, Germany
| | - Stefanie Dimmeler
- Institute of Cardiovascular Regeneration, Center of Molecular Medicine (A.T., L.S.T., A.F., M.M.-R., L.R.V., B.N.T., J.N., S.F.G., M.M., D.R.M., B.S., W.T.A., D.J., S.D., G.L.), Goethe University Frankfurt, Germany
- Cardiopulmonary Institute (A.T., L.S.T., S.F.G., M.M., S.K., B.S., S.G., W.T.A., D.J., I.F., N.W., S.D., G.L.), Goethe University Frankfurt, Germany
- German Center for Cardiovascular Research Deutsches Zentrum für Herz-Kreislauf-Forschung (DZHK), Frankfurt am Main, Germany (A.T., L.S.T., S.F.G., M.M., B.S., S.G., W.T.A., D.J., I.F., N.W., S.D., G.L.)
| | - Guillermo Luxán
- Institute of Cardiovascular Regeneration, Center of Molecular Medicine (A.T., L.S.T., A.F., M.M.-R., L.R.V., B.N.T., J.N., S.F.G., M.M., D.R.M., B.S., W.T.A., D.J., S.D., G.L.), Goethe University Frankfurt, Germany
- Cardiopulmonary Institute (A.T., L.S.T., S.F.G., M.M., S.K., B.S., S.G., W.T.A., D.J., I.F., N.W., S.D., G.L.), Goethe University Frankfurt, Germany
- German Center for Cardiovascular Research Deutsches Zentrum für Herz-Kreislauf-Forschung (DZHK), Frankfurt am Main, Germany (A.T., L.S.T., S.F.G., M.M., B.S., S.G., W.T.A., D.J., I.F., N.W., S.D., G.L.)
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24
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Ma J, Chu TK, Polo Prieto M, Park Y, Li Y, Chen R, Mardon G, Frankfort BJ, Tran NM. Sample multiplexing for retinal single-cell RNA-sequencing. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.23.589797. [PMID: 38712294 PMCID: PMC11071429 DOI: 10.1101/2024.04.23.589797] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Rare cell populations can be challenging to characterize using microfluidic single-cell RNA sequencing (scRNA-seq) platforms. Typically, the population of interest must be enriched and pooled from multiple biological specimens for efficient collection. However, these practices preclude the resolution of sample origin together with phenotypic data and are problematic in experiments in which biological or technical variation is expected to be high (e.g., disease models, genetic perturbation screens, or human samples). One solution is sample multiplexing whereby each sample is tagged with a unique sequence barcode that is resolved bioinformatically. We have established a scRNA-seq sample multiplexing pipeline for mouse retinal ganglion cells using cholesterol-modified-oligos and utilized the enhanced precision to investigate cell type distribution and transcriptomic variance across retinal samples. As single cell transcriptomics are becoming more widely used to research development and disease, sample multiplexing represents a useful method to enhance the precision of scRNA-seq analysis.
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25
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Pullin JM, McCarthy DJ. A comparison of marker gene selection methods for single-cell RNA sequencing data. Genome Biol 2024; 25:56. [PMID: 38409056 PMCID: PMC10895860 DOI: 10.1186/s13059-024-03183-0] [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: 09/13/2022] [Accepted: 02/07/2024] [Indexed: 02/28/2024] Open
Abstract
BACKGROUND The development of single-cell RNA sequencing (scRNA-seq) has enabled scientists to catalog and probe the transcriptional heterogeneity of individual cells in unprecedented detail. A common step in the analysis of scRNA-seq data is the selection of so-called marker genes, most commonly to enable annotation of the biological cell types present in the sample. In this paper, we benchmark 59 computational methods for selecting marker genes in scRNA-seq data. RESULTS We compare the performance of the methods using 14 real scRNA-seq datasets and over 170 additional simulated datasets. Methods are compared on their ability to recover simulated and expert-annotated marker genes, the predictive performance and characteristics of the gene sets they select, their memory usage and speed, and their implementation quality. In addition, various case studies are used to scrutinize the most commonly used methods, highlighting issues and inconsistencies. CONCLUSIONS Overall, we present a comprehensive evaluation of methods for selecting marker genes in scRNA-seq data. Our results highlight the efficacy of simple methods, especially the Wilcoxon rank-sum test, Student's t-test, and logistic regression.
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Affiliation(s)
- Jeffrey M Pullin
- Bioinformatics and Cellular Genomics, St Vincent's Institute of Medical Research, 9 Princes St, Fitzroy, 3065, VIC, Australia
- School of Mathematics and Statistics, University of Melbourne, Parkville, 3010, VIC, Australia
- Melbourne Integrative Genomics, University of Melbourne, Parkville, 3010, VIC, Australia
| | - Davis J McCarthy
- Bioinformatics and Cellular Genomics, St Vincent's Institute of Medical Research, 9 Princes St, Fitzroy, 3065, VIC, Australia.
- School of Mathematics and Statistics, University of Melbourne, Parkville, 3010, VIC, Australia.
- Melbourne Integrative Genomics, University of Melbourne, Parkville, 3010, VIC, Australia.
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26
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Monnier L, Cournède PH. A novel batch-effect correction method for scRNA-seq data based on Adversarial Information Factorization. PLoS Comput Biol 2024; 20:e1011880. [PMID: 38386700 PMCID: PMC10914288 DOI: 10.1371/journal.pcbi.1011880] [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: 07/21/2023] [Revised: 03/05/2024] [Accepted: 01/30/2024] [Indexed: 02/24/2024] Open
Abstract
Single-cell RNA sequencing (scRNA-seq) technology produces an unprecedented resolution at the level of a unique cell, raising great hopes in medicine. Nevertheless, scRNA-seq data suffer from high variations due to the experimental conditions, called batch effects, preventing any aggregated downstream analysis. Adversarial Information Factorization provides a robust batch-effect correction method that does not rely on prior knowledge of the cell types nor a specific normalization strategy while being adapted to any downstream analysis task. It compares to and even outperforms state-of-the-art methods in several scenarios: low signal-to-noise ratio, batch-specific cell types with few cells, and a multi-batches dataset with imbalanced batches and batch-specific cell types. Moreover, it best preserves the relative gene expression between cell types, yielding superior differential expression analysis results. Finally, in a more complex setting of a Leukemia cohort, our method preserved most of the underlying biological information for each patient while aligning the batches, improving the clustering metrics in the aggregated dataset.
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Affiliation(s)
- Lily Monnier
- Paris-Saclay University, CentraleSupélec, Laboratory of Mathematics and Computer Science (MICS), Gif-sur-Yvette, France
| | - Paul-Henry Cournède
- Paris-Saclay University, CentraleSupélec, Laboratory of Mathematics and Computer Science (MICS), Gif-sur-Yvette, France
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27
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Adegoke A, Ribeiro JMC, Smith R, Karim S. Tick innate immune responses to hematophagy and Ehrlichia infection at single-cell resolution. Front Immunol 2024; 14:1305976. [PMID: 38274813 PMCID: PMC10808623 DOI: 10.3389/fimmu.2023.1305976] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Accepted: 12/22/2023] [Indexed: 01/27/2024] Open
Abstract
Introduction Ticks rely on robust cellular and humoral responses to control microbial infection. However, several aspects of the tick's innate immune system remain uncharacterized, most notably that of the immune cells (called hemocytes), which are known to play a significant role in cellular and humoral responses. Despite the importance of hemocytes in regulating microbial infection, our understanding of their basic biology and molecular mechanisms remains limited. Therefore, we believe that a more detailed understanding of the role of hemocytes in the interactions between ticks and tick-borne microbes is crucial to illuminating their function in vector competence and to help identify novel targets for developing new strategies to block tick-borne pathogen transmission. Methods This study examined hemocytes from the lone star tick (Amblyomma americanum) at the transcriptomic level using the 10X genomics single-cell RNA sequencing platform to analyze hemocyte populations from unfed, partially blood-fed, and Ehrlichia chaffeensis-infected ticks. The functional role of differentially expressed hemocyte markers in hemocyte proliferation and Ehrlichia dissemination was determined using an RNA interference approach. Results and discussion Our data exhibit the identification of fourteen distinct hemocyte populations. Our results uncover seven distinct lineages present in uninfected and Ehrlichia-infected hemocyte clusters. The functional characterization of hemocytin, cystatin, fibronectin, and lipocalin demonstrate their role in hemocyte population changes, proliferation, and Ehrlichia dissemination. Conclusion Our results uncover the tick immune responses to Ehrlichia infection and hematophagy at a single-cell resolution. This work opens a new field of tick innate immunobiology to understand the role of hemocytes, particularly in response to prolonged blood-feeding (hematophagy), and tick-microbial interactions.
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Affiliation(s)
- Abdulsalam Adegoke
- School of Biological, Environmental, and Earth Sciences, The University of Southern Mississippi, Hattiesburg, MS, United States
| | - Jose M. C. Ribeiro
- Vector Biology Section, Laboratory of Malaria and Vector Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rockville, MD, United States
| | - Ryan C. Smith
- Department of Plant Pathology, Entomology, and Microbiology, Iowa State University, Ames, IA, United States
| | - Shahid Karim
- School of Biological, Environmental, and Earth Sciences, The University of Southern Mississippi, Hattiesburg, MS, United States
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28
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Feng J, Goedegebuure SP, Zeng A, Bi Y, Wang T, Payne P, Ding L, DeNardo D, Hawkins W, Fields RC, Li F. sc2MeNetDrug: A computational tool to uncover inter-cell signaling targets and identify relevant drugs based on single cell RNA-seq data. PLoS Comput Biol 2024; 20:e1011785. [PMID: 38181047 PMCID: PMC10796047 DOI: 10.1371/journal.pcbi.1011785] [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: 03/07/2023] [Revised: 01/18/2024] [Accepted: 12/23/2023] [Indexed: 01/07/2024] Open
Abstract
Single-cell RNA sequencing (scRNA-seq) is a powerful technology to investigate the transcriptional programs in stromal, immune, and disease cells, like tumor cells or neurons within the Alzheimer's Disease (AD) brain or tumor microenvironment (ME) or niche. Cell-cell communications within ME play important roles in disease progression and immunotherapy response and are novel and critical therapeutic targets. Though many tools of scRNA-seq analysis have been developed to investigate the heterogeneity and sub-populations of cells, few were designed for uncovering cell-cell communications of ME and predicting the potentially effective drugs to inhibit the communications. Moreover, the data analysis processes of discovering signaling communication networks and effective drugs using scRNA-seq data are complex and involve a set of critical analysis processes and external supportive data resources, which are difficult for researchers who have no strong computational background and training in scRNA-seq data analysis. To address these challenges, in this study, we developed a novel open-source computational tool, sc2MeNetDrug (https://fuhaililab.github.io/sc2MeNetDrug/). It was specifically designed using scRNA-seq data to identify cell types within disease MEs, uncover the dysfunctional signaling pathways within individual cell types and interactions among different cell types, and predict effective drugs that can potentially disrupt cell-cell signaling communications. sc2MeNetDrug provided a user-friendly graphical user interface to encapsulate the data analysis modules, which can facilitate the scRNA-seq data-based discovery of novel inter-cell signaling communications and novel therapeutic regimens.
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Affiliation(s)
- Jiarui Feng
- Institute for Informatics (I2), Washington University School of Medicine, Washington University in St. Louis, St. Louis, Missouri, United States of America
- Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, Missouri, United States of America
| | - S. Peter Goedegebuure
- Department of Surgery, Washington University in St. Louis, St. Louis, Missouri, United States of America
- Siteman Cancer Center, Washington University in St. Louis, St. Louis, Missouri, United States of America
| | - Amanda Zeng
- Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, Missouri, United States of America
| | - Ye Bi
- Department of Surgery, Washington University in St. Louis, St. Louis, Missouri, United States of America
| | - Ting Wang
- Department of Genetics, Washington University in St. Louis, St. Louis, Missouri, United States of America
- McDonnell Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America
| | - Philip Payne
- Institute for Informatics (I2), Washington University School of Medicine, Washington University in St. Louis, St. Louis, Missouri, United States of America
| | - Li Ding
- Siteman Cancer Center, Washington University in St. Louis, St. Louis, Missouri, United States of America
- Department of Genetics, Washington University in St. Louis, St. Louis, Missouri, United States of America
- McDonnell Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America
- Department of Medicine, Washington University in St. Louis, St. Louis, Missouri, United States of America
| | - David DeNardo
- Department of Surgery, Washington University in St. Louis, St. Louis, Missouri, United States of America
- Siteman Cancer Center, Washington University in St. Louis, St. Louis, Missouri, United States of America
| | - William Hawkins
- Department of Surgery, Washington University in St. Louis, St. Louis, Missouri, United States of America
- Siteman Cancer Center, Washington University in St. Louis, St. Louis, Missouri, United States of America
| | - Ryan C. Fields
- Department of Surgery, Washington University in St. Louis, St. Louis, Missouri, United States of America
- Siteman Cancer Center, Washington University in St. Louis, St. Louis, Missouri, United States of America
| | - Fuhai Li
- Institute for Informatics (I2), Washington University School of Medicine, Washington University in St. Louis, St. Louis, Missouri, United States of America
- Department of Pediatrics, Washington University School of Medicine, Washington University in St. Louis, St. Louis, Missouri, United States of America
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Zhu J, Yang Y. Imputation for Single-cell RNA-seq Data with Non-negative Matrix Factorization and Transfer Learning. J Bioinform Comput Biol 2023; 21:2350029. [PMID: 38248911 DOI: 10.1142/s0219720023500294] [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] [Indexed: 01/23/2024]
Abstract
Single-cell RNA sequencing (scRNA-seq) has been proven to be an effective technology for investigating the heterogeneity and transcriptome dynamics due to the single-cell resolution. However, one of the major problems for data obtained by scRNA-seq is excessive zeros in the count matrix, which hinders the downstream analysis enormously. Here, we present a method that integrates non-negative matrix factorization and transfer learning (NMFTL) to impute the scRNA-seq data. It borrows gene expression information from the additional dataset and adds graph-regularized terms to the decomposed matrices. These strategies not only maintain the intrinsic geometrical structure of the data itself but also further improve the accuracy of estimating the expression values by adding the transfer term in the model. The real data analysis result demonstrates that the proposed method outperforms the existing matrix-factorization-based imputation methods in recovering dropout entries, preserving gene-to-gene and cell-to-cell relationships, and in the downstream analysis, such as cell clustering analysis, the proposed method also has a good performance. For convenience, we have implemented the "NMFTL" method with R scripts, which could be available at https://github.com/FocusPaka/NMFTL.
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Affiliation(s)
- Jiadi Zhu
- School of Mathematics and Statistics, Xidian University, Xi'an, Shaanxi, P. R. China
| | - Youlong Yang
- School of Mathematics and Statistics, Xidian University, Xi'an, Shaanxi, P. R. China
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30
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Lu Y, Chen QM, An L. Semi-reference based cell type deconvolution with application to human metastatic cancers. NAR Genom Bioinform 2023; 5:lqad109. [PMID: 38143958 PMCID: PMC10748484 DOI: 10.1093/nargab/lqad109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 11/01/2023] [Accepted: 12/13/2023] [Indexed: 12/26/2023] Open
Abstract
Bulk RNA-seq experiments, commonly used to discern gene expression changes across conditions, often neglect critical cell type-specific information due to their focus on average transcript abundance. Recognizing cell type contribution is crucial to understanding phenotype and disease variations. The advent of single-cell RNA sequencing has allowed detailed examination of cellular heterogeneity; however, the cost and analytic caveat prohibits such sequencing for a large number of samples. We introduce a novel deconvolution approach, SECRET, that employs cell type-specific gene expression profiles from single-cell RNA-seq to accurately estimate cell type proportions from bulk RNA-seq data. Notably, SECRET can adapt to scenarios where the cell type present in the bulk data is unrepresented in the reference, thereby offering increased flexibility in reference selection. SECRET has demonstrated superior accuracy compared to existing methods using synthetic data and has identified unknown tissue-specific cell types in real human metastatic cancers. Its versatility makes it broadly applicable across various human cancer studies.
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Affiliation(s)
- Yingying Lu
- Interdisciplinary Program in Statistics and Data Science, University of Arizona, Tucson, AZ, USA
| | - Qin M Chen
- College of Pharmacy, University of Arizona, Tucson, AZ, USA
- Cancer Biology Program, University of Arizona, Tucson, AZ, USA
| | - Lingling An
- Interdisciplinary Program in Statistics and Data Science, University of Arizona, Tucson, AZ, USA
- Department of Biosystems Engineering, University of Arizona, Tucson, AZ, USA
- Department of Epidemiology and Biostatistics, University of Arizona, Tucson, AZ, USA
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31
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Sun T, Grassam-Rowe A, Pu Z, Li Y, Ren H, An Y, Guo X, Hu W, Liu Y, Zheng Y, Liu Z, Kou K, Ou X, Chen T, Fan X, Liu Y, Tu S, He Y, Ren Y, Chen A, Shang Z, Xia Z, Miquerol L, Smart N, Zhang H, Tan X, Shou W, Lei M. Dbh + catecholaminergic cardiomyocytes contribute to the structure and function of the cardiac conduction system in murine heart. Nat Commun 2023; 14:7801. [PMID: 38016975 PMCID: PMC10684617 DOI: 10.1038/s41467-023-42658-9] [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: 12/19/2022] [Accepted: 10/18/2023] [Indexed: 11/30/2023] Open
Abstract
The heterogeneity of functional cardiomyocytes arises during heart development, which is essential to the complex and highly coordinated cardiac physiological function. Yet the biological and physiological identities and the origin of the specialized cardiomyocyte populations have not been fully comprehended. Here we report a previously unrecognised population of cardiomyocytes expressing Dbhgene encoding dopamine beta-hydroxylase in murine heart. We determined how these myocytes are distributed across the heart by utilising advanced single-cell and spatial transcriptomic analyses, genetic fate mapping and molecular imaging with computational reconstruction. We demonstrated that they form the key functional components of the cardiac conduction system by using optogenetic electrophysiology and conditional cardiomyocyte Dbh gene deletion models. We revealed their close relationship with sympathetic innervation during cardiac conduction system formation. Our study thus provides new insights into the development and heterogeneity of the mammalian cardiac conduction system by revealing a new cardiomyocyte population with potential catecholaminergic endocrine function.
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Affiliation(s)
- Tianyi Sun
- Department of Pharmacology, University of Oxford, Mansfield Road, Oxford, OX1 3QT, UK
| | | | - Zhaoli Pu
- Key Laboratory of Medical Electrophysiology of the Ministry of Education, and Medical Electrophysiological Key Laboratory of Sichuan Province, Institute of Cardiovascular Research, Southwest Medical University, Luzhou, Sichuan, 646000, China
- Department of Cardiology, the Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, 646000, China
| | - Yangpeng Li
- Key Laboratory of Medical Electrophysiology of the Ministry of Education, and Medical Electrophysiological Key Laboratory of Sichuan Province, Institute of Cardiovascular Research, Southwest Medical University, Luzhou, Sichuan, 646000, China
- Department of Cardiology, the Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, 646000, China
| | - Huiying Ren
- Key Laboratory of Medical Electrophysiology of the Ministry of Education, and Medical Electrophysiological Key Laboratory of Sichuan Province, Institute of Cardiovascular Research, Southwest Medical University, Luzhou, Sichuan, 646000, China
- Department of Physiology, School of Basic Medical Sciences, Southwest Medical University, Luzhou, Sichuan, 646000, China
| | - Yanru An
- BGI Research, Shenzhen, 518103, China
| | - Xinyu Guo
- BGI Research, Qingdao, 266555, China
| | - Wei Hu
- Department of Physics & Astronomy, The University of Manchester, Brunswick Street, Manchester, M13 9PL, UK
| | - Ying Liu
- Herman B Wells Center for Pediatric Research, Department of Pediatrics, Indiana University School of Medicine, Indianapolis, USA
| | - Yuqing Zheng
- Key Laboratory of Medical Electrophysiology of the Ministry of Education, and Medical Electrophysiological Key Laboratory of Sichuan Province, Institute of Cardiovascular Research, Southwest Medical University, Luzhou, Sichuan, 646000, China
- Department of Cardiology, the Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, 646000, China
| | - Zhu Liu
- Key Laboratory of Medical Electrophysiology of the Ministry of Education, and Medical Electrophysiological Key Laboratory of Sichuan Province, Institute of Cardiovascular Research, Southwest Medical University, Luzhou, Sichuan, 646000, China
- Department of Cardiology, the Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, 646000, China
| | - Kun Kou
- Key Laboratory of Medical Electrophysiology of the Ministry of Education, and Medical Electrophysiological Key Laboratory of Sichuan Province, Institute of Cardiovascular Research, Southwest Medical University, Luzhou, Sichuan, 646000, China
- Department of Cardiology, the Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, 646000, China
| | - Xianhong Ou
- Key Laboratory of Medical Electrophysiology of the Ministry of Education, and Medical Electrophysiological Key Laboratory of Sichuan Province, Institute of Cardiovascular Research, Southwest Medical University, Luzhou, Sichuan, 646000, China
| | - Tangting Chen
- Key Laboratory of Medical Electrophysiology of the Ministry of Education, and Medical Electrophysiological Key Laboratory of Sichuan Province, Institute of Cardiovascular Research, Southwest Medical University, Luzhou, Sichuan, 646000, China
| | - Xuehui Fan
- Key Laboratory of Medical Electrophysiology of the Ministry of Education, and Medical Electrophysiological Key Laboratory of Sichuan Province, Institute of Cardiovascular Research, Southwest Medical University, Luzhou, Sichuan, 646000, China
| | - Yangyang Liu
- Herman B Wells Center for Pediatric Research, Department of Pediatrics, Indiana University School of Medicine, Indianapolis, USA
| | - Shu Tu
- Department of Pharmacology, University of Oxford, Mansfield Road, Oxford, OX1 3QT, UK
| | - Yu He
- Department of Pharmacology, University of Oxford, Mansfield Road, Oxford, OX1 3QT, UK
| | - Yue Ren
- Department of Pharmacology, University of Oxford, Mansfield Road, Oxford, OX1 3QT, UK
| | - Ao Chen
- BGI Research, Shenzhen, 518103, China
| | | | - Zhidao Xia
- Centre for Nanohealth, Swansea University Medical School, Swansea University, Singleton Park, Swansea, SA2 8PP, UK
| | - Lucile Miquerol
- Aix Marseille University, CNRS Institut de Biologie du Développement de Marseille UMR 7288, 13288, Marseille, France
| | - Nicola Smart
- Department of Physiology, Anatomy & Genetics, Sherrington Building, Oxford, University of, Oxford, OX1 3PT, UK
| | - Henggui Zhang
- Department of Physics & Astronomy, The University of Manchester, Brunswick Street, Manchester, M13 9PL, UK
- Beijing Academy of Artificial Intelligence, 100084, Beijing, China
| | - Xiaoqiu Tan
- Key Laboratory of Medical Electrophysiology of the Ministry of Education, and Medical Electrophysiological Key Laboratory of Sichuan Province, Institute of Cardiovascular Research, Southwest Medical University, Luzhou, Sichuan, 646000, China.
- Department of Cardiology, the Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, 646000, China.
- Department of Physiology, School of Basic Medical Sciences, Southwest Medical University, Luzhou, Sichuan, 646000, China.
| | - Weinian Shou
- Herman B Wells Center for Pediatric Research, Department of Pediatrics, Indiana University School of Medicine, Indianapolis, USA.
| | - Ming Lei
- Department of Pharmacology, University of Oxford, Mansfield Road, Oxford, OX1 3QT, UK.
- Key Laboratory of Medical Electrophysiology of the Ministry of Education, and Medical Electrophysiological Key Laboratory of Sichuan Province, Institute of Cardiovascular Research, Southwest Medical University, Luzhou, Sichuan, 646000, China.
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Tzaferis C, Karatzas E, Baltoumas FA, Pavlopoulos GA, Kollias G, Konstantopoulos D. SCALA: A complete solution for multimodal analysis of single-cell Next Generation Sequencing data. Comput Struct Biotechnol J 2023; 21:5382-5393. [PMID: 38022693 PMCID: PMC10651449 DOI: 10.1016/j.csbj.2023.10.032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2023] [Revised: 10/16/2023] [Accepted: 10/16/2023] [Indexed: 12/01/2023] Open
Abstract
Analysis and interpretation of high-throughput transcriptional and chromatin accessibility data at single-cell (sc) resolution are still open challenges in the biomedical field. The existence of countless bioinformatics tools, for the different analytical steps, increases the complexity of data interpretation and the difficulty to derive biological insights. In this article, we present SCALA, a bioinformatics tool for analysis and visualization of single-cell RNA sequencing (scRNA-seq) and Assay for Transposase-Accessible Chromatin using sequencing (scATAC-seq) datasets, enabling either independent or integrative analysis of the two modalities. SCALA combines standard types of analysis by integrating multiple software packages varying from quality control to the identification of distinct cell populations and cell states. Additional analysis options enable functional enrichment, cellular trajectory inference, ligand-receptor analysis, and regulatory network reconstruction. SCALA is fully parameterizable, presenting data in tabular format and producing publication-ready visualizations. The different available analysis modules can aid biomedical researchers in exploring, analyzing, and visualizing their data without any prior experience in coding. We demonstrate the functionality of SCALA through two use-cases related to TNF-driven arthritic mice, handling both scRNA-seq and scATAC-seq datasets. SCALA is developed in R, Shiny and JavaScript and is mainly available as a standalone version, while an online service of more limited capacity can be found at http://scala.pavlopouloslab.info or https://scala.fleming.gr.
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Affiliation(s)
- Christos Tzaferis
- Institute for Bioinnovation, Biomedical Sciences Research Center "Alexander Fleming", Vari, Greece
| | - Evangelos Karatzas
- Institute for Fundamental Biomedical Research, Biomedical Sciences Research Center "Alexander Fleming", Vari, Greece
| | - Fotis A. Baltoumas
- Institute for Fundamental Biomedical Research, Biomedical Sciences Research Center "Alexander Fleming", Vari, Greece
| | - Georgios A. Pavlopoulos
- Institute for Fundamental Biomedical Research, Biomedical Sciences Research Center "Alexander Fleming", Vari, Greece
- Research Institute of New Biotechnologies and Precision Medicine, National and Kapodistrian University of Athens, Greece
| | - George Kollias
- Institute for Bioinnovation, Biomedical Sciences Research Center "Alexander Fleming", Vari, Greece
- Research Institute of New Biotechnologies and Precision Medicine, National and Kapodistrian University of Athens, Greece
- Department of Physiology, Medical School, National and Kapodistrian University of Athens, Greece
| | - Dimitris Konstantopoulos
- Institute for Bioinnovation, Biomedical Sciences Research Center "Alexander Fleming", Vari, Greece
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Mooring M, Yeung GA, Luukkonen P, Liu S, Akbar MW, Zhang GJ, Balogun O, Yu X, Mo R, Nejak-Bowen K, Poyurovsky MV, Booth CJ, Konnikova L, Shulman GI, Yimlamai D. Hepatocyte CYR61 polarizes profibrotic macrophages to orchestrate NASH fibrosis. Sci Transl Med 2023; 15:eade3157. [PMID: 37756381 PMCID: PMC10874639 DOI: 10.1126/scitranslmed.ade3157] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Accepted: 08/18/2023] [Indexed: 09/29/2023]
Abstract
Obesity is increasing worldwide and leads to a multitude of metabolic diseases, including cardiovascular disease, type 2 diabetes, nonalcoholic fatty liver disease, and nonalcoholic steatohepatitis (NASH). Cysteine-rich angiogenic inducer 61 (CYR61) is associated with the progression of NASH, but it has been described to have anti- and proinflammatory properties. We sought to examine the role of liver CYR61 in NASH progression. CYR61 liver-specific knockout mice on a NASH diet showed improved glucose tolerance, decreased liver inflammation, and reduced fibrosis. CYR61 polarized infiltrating monocytes promoting a proinflammatory/profibrotic phenotype through an IRAK4/SYK/NF-κB signaling cascade. In vitro, CYR61 activated a profibrotic program, including PDGFa/PDGFb expression in macrophages, in an IRAK4/SYK/NF-κB-dependent manner. Furthermore, targeted-antibody blockade reduced CYR61-driven signaling in macrophages in vitro and in vivo, reducing fibrotic development. This study demonstrates that CYR61 is a key driver of liver inflammation and fibrosis in NASH.
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Affiliation(s)
- Meghan Mooring
- Department of Cellular and Molecular Pathology, University of Pittsburgh, School of Medicine; Pittsburgh, Pennsylvania 15261, USA
- Section of Pediatric Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics; Yale School of Medicine; New Haven, Connecticut 06514, USA
- These authors contributed equally to this work
| | - Grace A. Yeung
- Section of Pediatric Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics; Yale School of Medicine; New Haven, Connecticut 06514, USA
- These authors contributed equally to this work
| | - Panu Luukkonen
- Department of Internal Medicine, Yale School of Medicine; New Haven, Connecticut 06514, USA
| | - Silvia Liu
- Department of Pathology, School of Medicine, University of Pittsburgh
- Pittsburgh Liver Research Center, University of Pittsburgh, School of Medicine; Pittsburgh, Pennsylvania 15261, USA
| | - Muhammad Waqas Akbar
- Section of Pediatric Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics; Yale School of Medicine; New Haven, Connecticut 06514, USA
| | - Gary J. Zhang
- Section of Pediatric Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics; Yale School of Medicine; New Haven, Connecticut 06514, USA
| | - Oluwashanu Balogun
- Department of Cellular and Molecular Pathology, University of Pittsburgh, School of Medicine; Pittsburgh, Pennsylvania 15261, USA
- Department of Pathology, School of Medicine, University of Pittsburgh
| | - Xuemei Yu
- Kadmon Corporation, LLC; 450 East 29th Street, New York, New York 10016, USA
| | - Rigen Mo
- Kadmon Corporation, LLC; 450 East 29th Street, New York, New York 10016, USA
| | - Kari Nejak-Bowen
- Department of Cellular and Molecular Pathology, University of Pittsburgh, School of Medicine; Pittsburgh, Pennsylvania 15261, USA
- Department of Pathology, School of Medicine, University of Pittsburgh
- Pittsburgh Liver Research Center, University of Pittsburgh, School of Medicine; Pittsburgh, Pennsylvania 15261, USA
| | - Masha V. Poyurovsky
- Kadmon Corporation, LLC; 450 East 29th Street, New York, New York 10016, USA
| | - Carmen J. Booth
- Department of Comparative Medicine; Yale School of Medicine; New Haven, Connecticut 06514, USA
| | - Liza Konnikova
- Section of Neonatology; Department of Pediatrics; Yale School of Medicine; New Haven, Connecticut 06514, USA
| | - Gerald I. Shulman
- Department of Internal Medicine, Yale School of Medicine; New Haven, Connecticut 06514, USA
- Department of Cellular & Molecular Physiology, Yale School of Medicine; New Haven, Connecticut 06514, USA
| | - Dean Yimlamai
- Department of Cellular and Molecular Pathology, University of Pittsburgh, School of Medicine; Pittsburgh, Pennsylvania 15261, USA
- Section of Pediatric Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics; Yale School of Medicine; New Haven, Connecticut 06514, USA
- Pittsburgh Liver Research Center, University of Pittsburgh, School of Medicine; Pittsburgh, Pennsylvania 15261, USA
- The Yale Liver Center, Yale School of Medicine; New Haven, Connecticut 06514, USA
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Wang T, Zhao H, Xu Y, Wang Y, Shang X, Peng J, Xiao B. scMultiGAN: cell-specific imputation for single-cell transcriptomes with multiple deep generative adversarial networks. Brief Bioinform 2023; 24:bbad384. [PMID: 37903416 PMCID: PMC11020228 DOI: 10.1093/bib/bbad384] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Revised: 09/13/2023] [Accepted: 10/03/2023] [Indexed: 11/01/2023] Open
Abstract
The emergence of single-cell RNA sequencing (scRNA-seq) technology has revolutionized the identification of cell types and the study of cellular states at a single-cell level. Despite its significant potential, scRNA-seq data analysis is plagued by the issue of missing values. Many existing imputation methods rely on simplistic data distribution assumptions while ignoring the intrinsic gene expression distribution specific to cells. This work presents a novel deep-learning model, named scMultiGAN, for scRNA-seq imputation, which utilizes multiple collaborative generative adversarial networks (GAN). Unlike traditional GAN-based imputation methods that generate missing values based on random noises, scMultiGAN employs a two-stage training process and utilizes multiple GANs to achieve cell-specific imputation. Experimental results show the efficacy of scMultiGAN in imputation accuracy, cell clustering, differential gene expression analysis and trajectory analysis, significantly outperforming existing state-of-the-art techniques. Additionally, scMultiGAN is scalable to large scRNA-seq datasets and consistently performs well across sequencing platforms. The scMultiGAN code is freely available at https://github.com/Galaxy8172/scMultiGAN.
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Affiliation(s)
- Tao Wang
- School of Computer Science, Northwestern Polytechnical University, 1 Dongxiang Rd., 710072 Xi’an, China
- Key Laboratory of Big Data Storage and Management, Ministry of Industry and Information Technology, Northwestern Polytechnical University, 1 Dongxiang Rd., 710072 Xi’an, China
| | - Hui Zhao
- School of Automation, Northwestern Polytechnical University, 1 Dongxiang Rd., 710072 Xi’an, China
| | - Yungang Xu
- Department of Cell Biology and Genetics, School of Basic Medical Sciences, Xi’an Jiaotong University Health Science Center, No.28, West Xianning Road, 710061 Xi’an, China
| | - Yongtian Wang
- School of Computer Science, Northwestern Polytechnical University, 1 Dongxiang Rd., 710072 Xi’an, China
- Key Laboratory of Big Data Storage and Management, Ministry of Industry and Information Technology, Northwestern Polytechnical University, 1 Dongxiang Rd., 710072 Xi’an, China
| | - Xuequn Shang
- School of Computer Science, Northwestern Polytechnical University, 1 Dongxiang Rd., 710072 Xi’an, China
- Key Laboratory of Big Data Storage and Management, Ministry of Industry and Information Technology, Northwestern Polytechnical University, 1 Dongxiang Rd., 710072 Xi’an, China
| | - Jiajie Peng
- School of Computer Science, Northwestern Polytechnical University, 1 Dongxiang Rd., 710072 Xi’an, China
- Key Laboratory of Big Data Storage and Management, Ministry of Industry and Information Technology, Northwestern Polytechnical University, 1 Dongxiang Rd., 710072 Xi’an, China
| | - Bing Xiao
- School of Automation, Northwestern Polytechnical University, 1 Dongxiang Rd., 710072 Xi’an, China
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Causer A, Tan X, Lu X, Moseley P, Teoh SM, Molotkov N, McGrath M, Kim T, Simpson PT, Perry C, Frazer IH, Panizza B, Ladwa R, Nguyen Q, Gonzalez-Cruz JL. Deep spatial-omics analysis of Head & Neck carcinomas provides alternative therapeutic targets and rationale for treatment failure. NPJ Precis Oncol 2023; 7:89. [PMID: 37704757 PMCID: PMC10499928 DOI: 10.1038/s41698-023-00444-2] [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: 03/03/2023] [Accepted: 08/30/2023] [Indexed: 09/15/2023] Open
Abstract
Immune checkpoint inhibitor (ICI) therapy has had limited success (<30%) in treating metastatic recurrent Head and Neck Oropharyngeal Squamous Cell Carcinomas (OPSCCs). We postulate that spatial determinants in the tumor play a critical role in cancer therapy outcomes. Here, we describe the case of a male patient diagnosed with p16+ OPSCC and extensive lung metastatic disease who failed Nivolumab and Pembrolizumab/Lenvatinib therapies. Using advanced integrative spatial proteogenomic analysis on the patient's recurrent OPSCC tumors we demonstrate that: (i) unbiased tissue clustering based on spatial transcriptomics (ST) successfully detected tumor cells and enabled the investigation of phenotypic traits such as proliferation or drug-resistance genes in the tumor's leading-edge and core; (ii) spatial proteomic imagining used in conjunction with ST (SpiCi, Spatial Proteomics inferred Cell identification) can resolve the profiling of tumor infiltrating immune cells, (iii) ST data allows for the discovery and ranking of clinically relevant alternative medicines based on their interaction with their matching ligand-receptor. Importantly, when the spatial profiles of ICI pre- and post-failure OPSCC tumors were compared, they exhibited highly similar PD-1/PD-L1low and VEGFAhigh expression, suggesting that these new tumors were not the product of ICI resistance but rather of Lenvatinib dose reduction due to complications. Our work establishes a path for incorporating spatial-omics in clinical settings to facilitate treatment personalization.
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Affiliation(s)
- Andrew Causer
- Institute of Molecular Biology, The University of Queensland, Brisbane, QLD, Australia
| | - Xiao Tan
- Frazer Institute, The University of Queensland, Brisbane, QLD, Australia
| | - Xuehan Lu
- Frazer Institute, The University of Queensland, Brisbane, QLD, Australia
| | - Philip Moseley
- Frazer Institute, The University of Queensland, Brisbane, QLD, Australia
| | - Siok M Teoh
- Institute of Molecular Biology, The University of Queensland, Brisbane, QLD, Australia
| | - Natalie Molotkov
- Frazer Institute, The University of Queensland, Brisbane, QLD, Australia
| | - Margaret McGrath
- Department of Medical Oncology, Princess Alexandra Hospital, Brisbane, QLD, Australia
| | - Taehyun Kim
- Pathology Queensland, Royal Brisbane & Women's Hospital, Brisbane, QLD, Australia
| | - Peter T Simpson
- UQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
| | - Christopher Perry
- Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
- Department of Otolaryngology-Head & Neck surgery, Princess Alexandra Hospital, Brisbane, QLD, Australia
| | - Ian H Frazer
- Frazer Institute, The University of Queensland, Brisbane, QLD, Australia
| | - Benedict Panizza
- Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
- Department of Otolaryngology-Head & Neck surgery, Princess Alexandra Hospital, Brisbane, QLD, Australia
| | - Rahul Ladwa
- Department of Medical Oncology, Princess Alexandra Hospital, Brisbane, QLD, Australia
- Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
| | - Quan Nguyen
- Institute of Molecular Biology, The University of Queensland, Brisbane, QLD, Australia.
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He T, Guo W, Yang G, Su H, Dou A, Chen L, Ma T, Su J, Liu M, Su B, Qi W, Li H, Mao W, Wang X, Li X, Yang Y, Song Y, Cao G. A Single-Cell Atlas of an Early Mongolian Sheep Embryo. Vet Sci 2023; 10:543. [PMID: 37756065 PMCID: PMC10536297 DOI: 10.3390/vetsci10090543] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 07/25/2023] [Accepted: 08/22/2023] [Indexed: 09/28/2023] Open
Abstract
Cell types have been established during organogenesis based on early mouse embryos. However, our understanding of cell types and molecular mechanisms in the early embryo development of Mongolian sheep has been hampered. This study presents the first comprehensive single-cell transcriptomic characterization at E16 in Ujumqin sheep and Hulunbuir short-tailed sheep. Thirteen major cell types were identified at E16 in Ujumqin sheep, and eight major cell types were identified at E16 in Hulunbuir short-tailed sheep. Function enrichment analysis showed that several pathways were significantly enriched in the TGF-beta signaling pathway, the Hippo signaling pathway, the platelet activation pathway, the riboflavin metabolism pathway, the Wnt signaling pathway, regulation of the actin cytoskeleton, and the insulin signaling pathway in the notochord cluster. Glutathione metabolism, glyoxylate, and dicarboxylate metabolism, the citrate cycle, thyroid hormone synthesis, pyruvate metabolism, cysteine and methionine metabolism, thermogenesis, and the VEGF signaling pathway were significantly enriched in the spinal cord cluster. Steroid biosynthesis, riboflavin metabolism, the cell cycle, the Hippo signaling pathway, the Hedgehog signaling pathway, the FoxO signaling pathway, the JAK-STAT signaling pathway, and the Wnt signaling pathway were significantly enriched in the paraxial mesoderm cluster. The notochord cluster, spinal cord cluster, and paraxial mesoderm cluster were found to be highly associated with tail development. Pseudo-time analysis demonstrated that the mesenchyme can translate to the notochord in Ujumqin sheep. Molecular assays revealed that the Hippo signaling pathway was enriched in Ujumqin sheep. This comprehensive single-cell map revealed previously unrecognized signaling pathways that will further our understanding of the mechanism of short-tailed sheep formation.
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Affiliation(s)
- Tingyi He
- Inner Mongolia Key Laboratory of Basic Veterinary Medicine, Key Laboratory of Animal Embryo, and Development Engineering Autonomous Region, Inner Mongolia Agricultural University, Hohhot 010018, China; (T.H.); (W.G.); (H.S.); (A.D.); (L.C.); (T.M.); (M.L.); (B.S.); (W.Q.); (H.L.); (W.M.); (X.W.)
- Institute of Animal Husbandry, Inner Mongolia Academy of Agricultural and Animal Husbandry Sciences, Huhhot 010031, China
| | - Wenrui Guo
- Inner Mongolia Key Laboratory of Basic Veterinary Medicine, Key Laboratory of Animal Embryo, and Development Engineering Autonomous Region, Inner Mongolia Agricultural University, Hohhot 010018, China; (T.H.); (W.G.); (H.S.); (A.D.); (L.C.); (T.M.); (M.L.); (B.S.); (W.Q.); (H.L.); (W.M.); (X.W.)
| | - Guang Yang
- The State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, College of Life Sciences, Inner Mongolia University, Hohhot 010020, China; (G.Y.); (X.L.)
- Research Center for Animal Genetic Resources of Mongolia Plateau, College of Life Science, Inner Mongolia University, Hohhot 010020, China
| | - Hong Su
- Inner Mongolia Key Laboratory of Basic Veterinary Medicine, Key Laboratory of Animal Embryo, and Development Engineering Autonomous Region, Inner Mongolia Agricultural University, Hohhot 010018, China; (T.H.); (W.G.); (H.S.); (A.D.); (L.C.); (T.M.); (M.L.); (B.S.); (W.Q.); (H.L.); (W.M.); (X.W.)
| | - Aolei Dou
- Inner Mongolia Key Laboratory of Basic Veterinary Medicine, Key Laboratory of Animal Embryo, and Development Engineering Autonomous Region, Inner Mongolia Agricultural University, Hohhot 010018, China; (T.H.); (W.G.); (H.S.); (A.D.); (L.C.); (T.M.); (M.L.); (B.S.); (W.Q.); (H.L.); (W.M.); (X.W.)
| | - Lu Chen
- Inner Mongolia Key Laboratory of Basic Veterinary Medicine, Key Laboratory of Animal Embryo, and Development Engineering Autonomous Region, Inner Mongolia Agricultural University, Hohhot 010018, China; (T.H.); (W.G.); (H.S.); (A.D.); (L.C.); (T.M.); (M.L.); (B.S.); (W.Q.); (H.L.); (W.M.); (X.W.)
| | - Teng Ma
- Inner Mongolia Key Laboratory of Basic Veterinary Medicine, Key Laboratory of Animal Embryo, and Development Engineering Autonomous Region, Inner Mongolia Agricultural University, Hohhot 010018, China; (T.H.); (W.G.); (H.S.); (A.D.); (L.C.); (T.M.); (M.L.); (B.S.); (W.Q.); (H.L.); (W.M.); (X.W.)
| | - Jie Su
- Department of Medical Neurobiology, Inner Mongolia Medical University, Huhhot 010030, China;
| | - Moning Liu
- Inner Mongolia Key Laboratory of Basic Veterinary Medicine, Key Laboratory of Animal Embryo, and Development Engineering Autonomous Region, Inner Mongolia Agricultural University, Hohhot 010018, China; (T.H.); (W.G.); (H.S.); (A.D.); (L.C.); (T.M.); (M.L.); (B.S.); (W.Q.); (H.L.); (W.M.); (X.W.)
| | - Budeng Su
- Inner Mongolia Key Laboratory of Basic Veterinary Medicine, Key Laboratory of Animal Embryo, and Development Engineering Autonomous Region, Inner Mongolia Agricultural University, Hohhot 010018, China; (T.H.); (W.G.); (H.S.); (A.D.); (L.C.); (T.M.); (M.L.); (B.S.); (W.Q.); (H.L.); (W.M.); (X.W.)
| | - Wangmei Qi
- Inner Mongolia Key Laboratory of Basic Veterinary Medicine, Key Laboratory of Animal Embryo, and Development Engineering Autonomous Region, Inner Mongolia Agricultural University, Hohhot 010018, China; (T.H.); (W.G.); (H.S.); (A.D.); (L.C.); (T.M.); (M.L.); (B.S.); (W.Q.); (H.L.); (W.M.); (X.W.)
| | - Haijun Li
- Inner Mongolia Key Laboratory of Basic Veterinary Medicine, Key Laboratory of Animal Embryo, and Development Engineering Autonomous Region, Inner Mongolia Agricultural University, Hohhot 010018, China; (T.H.); (W.G.); (H.S.); (A.D.); (L.C.); (T.M.); (M.L.); (B.S.); (W.Q.); (H.L.); (W.M.); (X.W.)
| | - Wei Mao
- Inner Mongolia Key Laboratory of Basic Veterinary Medicine, Key Laboratory of Animal Embryo, and Development Engineering Autonomous Region, Inner Mongolia Agricultural University, Hohhot 010018, China; (T.H.); (W.G.); (H.S.); (A.D.); (L.C.); (T.M.); (M.L.); (B.S.); (W.Q.); (H.L.); (W.M.); (X.W.)
| | - Xiumei Wang
- Inner Mongolia Key Laboratory of Basic Veterinary Medicine, Key Laboratory of Animal Embryo, and Development Engineering Autonomous Region, Inner Mongolia Agricultural University, Hohhot 010018, China; (T.H.); (W.G.); (H.S.); (A.D.); (L.C.); (T.M.); (M.L.); (B.S.); (W.Q.); (H.L.); (W.M.); (X.W.)
| | - Xihe Li
- The State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, College of Life Sciences, Inner Mongolia University, Hohhot 010020, China; (G.Y.); (X.L.)
- Research Center for Animal Genetic Resources of Mongolia Plateau, College of Life Science, Inner Mongolia University, Hohhot 010020, China
| | - Yanyan Yang
- Institute of Animal Husbandry, Inner Mongolia Academy of Agricultural and Animal Husbandry Sciences, Huhhot 010031, China
| | - Yongli Song
- The State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, College of Life Sciences, Inner Mongolia University, Hohhot 010020, China; (G.Y.); (X.L.)
- Research Center for Animal Genetic Resources of Mongolia Plateau, College of Life Science, Inner Mongolia University, Hohhot 010020, China
| | - Guifang Cao
- Inner Mongolia Key Laboratory of Basic Veterinary Medicine, Key Laboratory of Animal Embryo, and Development Engineering Autonomous Region, Inner Mongolia Agricultural University, Hohhot 010018, China; (T.H.); (W.G.); (H.S.); (A.D.); (L.C.); (T.M.); (M.L.); (B.S.); (W.Q.); (H.L.); (W.M.); (X.W.)
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37
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Song D, Li K, Ge X, Li JJ. ClusterDE: a post-clustering differential expression (DE) method robust to false-positive inflation caused by double dipping. RESEARCH SQUARE 2023:rs.3.rs-3211191. [PMID: 37577698 PMCID: PMC10418557 DOI: 10.21203/rs.3.rs-3211191/v1] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/15/2023]
Abstract
In typical single-cell RNA-seq (scRNA-seq) data analysis, a clustering algorithm is applied to find putative cell types as clusters, and then a statistical differential expression (DE) test is employed to identify the differentially expressed (DE) genes between the cell clusters. However, this common procedure uses the same data twice, an issue known as "double dipping": the same data is used twice to define cell clusters as potential cell types and DE genes as potential cell-type marker genes, leading to false-positive cell-type marker genes even when the cell clusters are spurious. To overcome this challenge, we propose ClusterDE, a post-clustering DE method for controlling the false discovery rate (FDR) of identified DE genes regardless of clustering quality, which can work as an add-on to popular pipelines such as Seurat. The core idea of ClusterDE is to generate real-data-based synthetic null data containing only one cluster, as contrast to the real data, for evaluating the whole procedure of clustering followed by a DE test. Using comprehensive simulation and real data analysis, we show that ClusterDE has not only solid FDR control but also the ability to identify cell-type marker genes as top DE genes and distinguish them from housekeeping genes. ClusterDE is fast, transparent, and adaptive to a wide range of clustering algorithms and DE tests. Besides scRNA-seq data, ClusterDE is generally applicable to post-clustering DE analysis, including single-cell multi-omics data analysis.
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Affiliation(s)
- Dongyuan Song
- Bioinformatics Interdepartmental Ph.D. Program, University of California, Los Angeles, CA 90095-7246
| | - Kexin Li
- Department of Statistics, University of California, Los Angeles, CA 90095-1554
| | - Xinzhou Ge
- Department of Statistics, University of California, Los Angeles, CA 90095-1554
| | - Jingyi Jessica Li
- Bioinformatics Interdepartmental Ph.D. Program, University of California, Los Angeles, CA 90095-7246
- Department of Statistics, University of California, Los Angeles, CA 90095-1554
- Department of Human Genetics, University of California, Los Angeles, CA 90095-7088
- Department of Computational Medicine, University of California, Los Angeles, CA 90095-1766
- Department of Biostatistics, University of California, Los Angeles, CA 90095-1772
- Radcliffe Institute for Advanced Study, Harvard University, Cambridge, MA 02138
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Xing L, Wang L, Liu S, Sun L, Wessel GM, Yang H. Single-Cell Transcriptome and Pigment Biochemistry Analysis Reveals the Potential for the High Nutritional and Medicinal Value of Purple Sea Cucumbers. Int J Mol Sci 2023; 24:12213. [PMID: 37569587 PMCID: PMC10419132 DOI: 10.3390/ijms241512213] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 07/25/2023] [Accepted: 07/26/2023] [Indexed: 08/13/2023] Open
Abstract
The sea cucumber Apostichopus japonicus has important nutritional and medicinal value. Unfortunately, we know little of the source of active chemicals in this animal, but the plentiful pigments of these animals are thought to function in intriguing ways for translation into clinical and food chemistry usage. Here, we found key cell groups with the gene activity predicted for the color morphology of sea cucumber body using single-cell RNA-seq. We refer to these cell populations as melanocytes and quinocytes, which are responsible for the synthesis of melanin and quinone pigments, respectively. We integrated analysis of pigment biochemistry with the transcript profiles to illuminate the molecular mechanisms regulating distinct pigment formation in echinoderms. In concert with the correlated pigment analysis from each color morph, this study expands our understanding of medically important pigment production, as well as the genetic mechanisms for color morphs, and provides deep datasets for exploring advancements in the fields of bioactives and nutraceuticals.
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Affiliation(s)
- Lili Xing
- CAS Key Laboratory of Marine Ecology and Environmental Sciences, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China; (L.X.); (S.L.); (H.Y.)
- CAS Engineering Laboratory for Marine Ranching, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Lingyu Wang
- Department of Biology, Duke University, Durham, NC 27708, USA;
| | - Shilin Liu
- CAS Key Laboratory of Marine Ecology and Environmental Sciences, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China; (L.X.); (S.L.); (H.Y.)
- CAS Engineering Laboratory for Marine Ranching, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Lina Sun
- CAS Key Laboratory of Marine Ecology and Environmental Sciences, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China; (L.X.); (S.L.); (H.Y.)
- CAS Engineering Laboratory for Marine Ranching, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Gary M. Wessel
- Department of Molecular Biology, Cellular Biology, and Biochemistry, Brown University, Providence, RI 02912, USA
| | - Hongsheng Yang
- CAS Key Laboratory of Marine Ecology and Environmental Sciences, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China; (L.X.); (S.L.); (H.Y.)
- CAS Engineering Laboratory for Marine Ranching, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
- University of Chinese Academy of Sciences, Beijing 100049, China
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Park CJ, Minabe S, Hess RA, Lin PCP, Zhou S, Bashir ST, Barakat R, Gal A, Ko CJ. Single neonatal estrogen implant sterilizes female animals by decreasing hypothalamic KISS1 expression. Sci Rep 2023; 13:9627. [PMID: 37316510 DOI: 10.1038/s41598-023-36727-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Accepted: 06/08/2023] [Indexed: 06/16/2023] Open
Abstract
Reproductive sterilization by surgical gonadectomy is strongly advocated to help manage animal populations, especially domesticated pets, and to prevent reproductive behaviors and diseases. This study explored the use of a single-injection method to induce sterility in female animals as an alternative to surgical ovariohysterectomy. The idea was based on our recent finding that repetitive daily injection of estrogen into neonatal rats disrupted hypothalamic expression of Kisspeptin (KISS1), the neuropeptide that triggers and regulates pulsatile secretion of GnRH. Neonatal female rats were dosed with estradiol benzoate (EB) either by daily injections for 11 days or by subcutaneous implantation of an EB-containing silicone capsule designed to release EB over 2-3 weeks. Rats treated by either method did not exhibit estrous cyclicity, were anovulatory, and became infertile. The EB-treated rats had fewer hypothalamic Kisspeptin neurons, but the GnRH-LH axis remained responsive to Kisspeptin stimulation. Because it would be desirable to use a biodegradable carrier that is also easier to handle, an injectable EB carrier was developed from PLGA microspheres to provide pharmacokinetics comparable to the EB-containing silicone capsule. A single neonatal injection of EB-microspheres at an equivalent dosage resulted in sterility in the female rat. In neonatal female Beagle dogs, implantation of an EB-containing silicone capsule also reduced ovarian follicle development and significantly inhibited KISS1 expression in the hypothalamus. None of the treatments produced any concerning health effects, other than infertility. Therefore, further development of this technology for sterilization in domestic female animals, such as dogs and cats is worthy of investigation.
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Affiliation(s)
- Chan Jin Park
- Department of Comparative Biosciences, College of Veterinary Medicine, University of Illinois at Urbana-Champaign, Urbana, IL, 61802, USA
- Epivara, Inc, Champaign, IL, 61820, USA
| | - Shiori Minabe
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Iwate, 028-3694, Japan
| | - Rex A Hess
- Department of Comparative Biosciences, College of Veterinary Medicine, University of Illinois at Urbana-Champaign, Urbana, IL, 61802, USA
- Epivara, Inc, Champaign, IL, 61820, USA
| | - Po-Ching Patrick Lin
- Department of Comparative Biosciences, College of Veterinary Medicine, University of Illinois at Urbana-Champaign, Urbana, IL, 61802, USA
| | | | - Shah Tauseef Bashir
- Department of Comparative Biosciences, College of Veterinary Medicine, University of Illinois at Urbana-Champaign, Urbana, IL, 61802, USA
| | - Radwa Barakat
- Department of Comparative Biosciences, College of Veterinary Medicine, University of Illinois at Urbana-Champaign, Urbana, IL, 61802, USA
- Department of Toxicology and Forensic Medicine, Faculty of Veterinary Medicine, Benha University, Qalyubia, 13518, Egypt
| | - Arnon Gal
- Department of Veterinary Clinical Medicine, College of Veterinary Medicine, University of Illinois at Urbana-Champaign, Urbana, IL, 61802, USA
| | - CheMyong Jay Ko
- Department of Comparative Biosciences, College of Veterinary Medicine, University of Illinois at Urbana-Champaign, Urbana, IL, 61802, USA.
- Epivara, Inc, Champaign, IL, 61820, USA.
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Diwanji R, O'Brien NA, Choi JE, Nguyen B, Laszewski T, Grauel AL, Yan Z, Xu X, Wu J, Ruddy DA, Piquet M, Pelletier MR, Savchenko A, Charette L, Rodrik-Outmezguine V, Baum J, Millholland JM, Wong CC, Martin AM, Dranoff G, Pruteanu-Malinici I, Cremasco V, Sabatos-Peyton C, Jayaraman P. Targeting the IL1β Pathway for Cancer Immunotherapy Remodels the Tumor Microenvironment and Enhances Antitumor Immune Responses. Cancer Immunol Res 2023; 11:777-791. [PMID: 37040466 DOI: 10.1158/2326-6066.cir-22-0290] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Revised: 12/14/2022] [Accepted: 04/07/2023] [Indexed: 04/13/2023]
Abstract
High levels of IL1β can result in chronic inflammation, which in turn can promote tumor growth and metastasis. Inhibition of IL1β could therefore be a promising therapeutic option in the treatment of cancer. Here, the effects of IL1β blockade induced by the mAbs canakinumab and gevokizumab were evaluated alone or in combination with docetaxel, anti-programmed cell death protein 1 (anti-PD-1), anti-VEGFα, and anti-TGFβ treatment in syngeneic and humanized mouse models of cancers of different origin. Canakinumab and gevokizumab did not show notable efficacy as single-agent therapies; however, IL1β blockade enhanced the effectiveness of docetaxel and anti-PD-1. Accompanying these effects, blockade of IL1β alone or in combination induced significant remodeling of the tumor microenvironment (TME), with decreased numbers of immune suppressive cells and increased tumor infiltration by dendritic cells (DC) and effector T cells. Further investigation revealed that cancer-associated fibroblasts (CAF) were the cell type most affected by treatment with canakinumab or gevokizumab in terms of change in gene expression. IL1β inhibition drove phenotypic changes in CAF populations, particularly those with the ability to influence immune cell recruitment. These results suggest that the observed remodeling of the TME following IL1β blockade may stem from changes in CAF populations. Overall, the results presented here support the potential use of IL1β inhibition in cancer treatment. Further exploration in ongoing clinical studies will help identify the best combination partners for different cancer types, cancer stages, and lines of treatment.
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Affiliation(s)
- Rohan Diwanji
- Immuno Oncology, Novartis Institutes for Biomedical Research, Cambridge, Massachusetts
| | - Neil A O'Brien
- Division of Hematology/Oncology, Department of Medicine, Geffen School of Medicine at University of California, Los Angeles (UCLA), Los Angeles, California
| | - Jiyoung E Choi
- Immuno Oncology, Novartis Institutes for Biomedical Research, Cambridge, Massachusetts
| | - Beverly Nguyen
- Immuno Oncology, Novartis Institutes for Biomedical Research, Cambridge, Massachusetts
| | - Tyler Laszewski
- Immuno Oncology, Novartis Institutes for Biomedical Research, Cambridge, Massachusetts
| | - Angelo L Grauel
- Immuno Oncology, Novartis Institutes for Biomedical Research, Cambridge, Massachusetts
| | - Zheng Yan
- Oncology Translational Research, Novartis Institutes for Biomedical Research, Cambridge, Massachusetts
| | - Xin Xu
- Oncology Data Sciences, Novartis Institutes for Biomedical Research, Cambridge, Massachusetts
| | - Jincheng Wu
- Oncology Data Sciences, Novartis Institutes for Biomedical Research, Cambridge, Massachusetts
| | - David A Ruddy
- Oncology, Novartis Institutes for Biomedical Research, Cambridge, Massachusetts
| | - Michelle Piquet
- Oncology, Novartis Institutes for Biomedical Research, Cambridge, Massachusetts
| | - Marc R Pelletier
- Oncology Translational Research, Novartis Institutes for Biomedical Research, Cambridge, Massachusetts
| | | | | | | | - Jason Baum
- Precision Medicine, Novartis Pharmaceuticals, Cambridge, Massachusetts
| | | | - Connie C Wong
- Precision Medicine, Novartis Pharmaceuticals, Cambridge, Massachusetts
| | - Anne-Marie Martin
- Precision Medicine, Novartis Pharmaceuticals, Cambridge, Massachusetts
| | - Glenn Dranoff
- Immuno Oncology, Novartis Institutes for Biomedical Research, Cambridge, Massachusetts
| | | | - Viviana Cremasco
- Immuno Oncology, Novartis Institutes for Biomedical Research, Cambridge, Massachusetts
| | | | - Pushpa Jayaraman
- Immuno Oncology, Novartis Institutes for Biomedical Research, Cambridge, Massachusetts
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Du J, Wang Y, Chen W, Xu M, Zhou R, Shou H, Chen J. High-resolution anatomical and spatial transcriptome analyses reveal two types of meristematic cell pools within the secondary vascular tissue of poplar stem. MOLECULAR PLANT 2023; 16:809-828. [PMID: 36895162 DOI: 10.1016/j.molp.2023.03.005] [Citation(s) in RCA: 38] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/23/2022] [Revised: 02/12/2023] [Accepted: 03/06/2023] [Indexed: 05/04/2023]
Abstract
The secondary vascular tissue emanating from meristems is central to understanding how vascular plants such as forest trees evolve, grow, and regulate secondary radial growth. However, the overall molecular characterization of meristem origins and developmental trajectories from primary to secondary vascular tissues in woody tree stems is technically challenging. In this study, we combined high-resolution anatomic analysis with a spatial transcriptome (ST) technique to define features of meristematic cells in a developmental gradient from primary to secondary vascular tissues in poplar stems. The tissue-specific gene expression of meristems and derived vascular tissue types were accordingly mapped to specific anatomical domains. Pseudotime analyses were used to track the origins and changes of meristems throughout the development from primary to secondary vascular tissues. Surprisingly, two types of meristematic-like cell pools within secondary vascular tissues were inferred based on high-resolution microscopy combined with ST, and the results were confirmed by in situ hybridization of, transgenic trees, and single-cell sequencing. The rectangle shape procambium-like (PCL) cells develop from procambium meristematic cells and are located within the phloem domain to produce phloem cells, whereas fusiform shape cambium zone (CZ) meristematic cells develop from fusiform metacambium meristematic cells and are located inside the CZ to produce xylem cells. The gene expression atlas and transcriptional networks spanning the primary transition to secondary vascular tissues generated in this work provide new resources for studying the regulation of meristem activities and the evolution of vascular plants. A web server (https://pgx.zju.edu.cn/stRNAPal/) was also established to facilitate the use of ST RNA-seq data.
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Affiliation(s)
- Juan Du
- State Key Laboratory of Plant Physiology and Biochemistry, College of Life Sciences, Zhejiang University, 866 Yu Hangtang Road, Hangzhou, Zhejiang 310058, China.
| | - Yichen Wang
- Hangzhou Botanical Garden, Taoyuanling Road, Hangzhou, Zhejiang 310013, China
| | - Wenfan Chen
- Institute of Quantitative Biology, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Mingling Xu
- State Key Laboratory of Plant Physiology and Biochemistry, College of Life Sciences, Zhejiang University, 866 Yu Hangtang Road, Hangzhou, Zhejiang 310058, China
| | - Ruhong Zhou
- MOE Key Laboratory of Biosystems Homeostasis & Protection, College of Life Sciences, Zhejiang University, 866 Yu Hangtang Road, Hangzhou, Zhejiang 310058, China; Institute of Quantitative Biology, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Huixia Shou
- State Key Laboratory of Plant Physiology and Biochemistry, College of Life Sciences, Zhejiang University, 866 Yu Hangtang Road, Hangzhou, Zhejiang 310058, China
| | - Jun Chen
- MOE Key Laboratory of Biosystems Homeostasis & Protection, College of Life Sciences, Zhejiang University, 866 Yu Hangtang Road, Hangzhou, Zhejiang 310058, China.
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Jia J, Zhao Y, Wang JH, Kuang YQ. Isolating peripheral blood mononuclear cells from HIV-infected patients for single-cell RNA sequencing and integration analysis. STAR Protoc 2023; 4:102222. [PMID: 37060557 PMCID: PMC10140154 DOI: 10.1016/j.xpro.2023.102222] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 02/21/2023] [Accepted: 03/15/2023] [Indexed: 04/16/2023] Open
Abstract
Single-cell RNA sequencing (scRNA-seq) of peripheral blood mononuclear cells (PBMCs) allows the dissection of transcriptional changes in immune cells with HIV infection. Here, we isolate PBMCs from HIV-infected individuals. After counting the cell number and verifying cell viability, we perform scRNA-seq for PBMCs on the 10× Genomics protocol and the Illumina NovaSeq 6000 sequencing platform. Furthermore, we analyze the function and cellular trajectories of B cell subsets and B cell receptor (BCR) repertoire after filtering raw sequences data and normalizing gene expression. For complete details on the use and execution of this protocol, please refer to Jia et al. (2022).1.
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Affiliation(s)
- Jie Jia
- NHC Key Laboratory of Drug Addiction Medicine, First Affiliated Hospital of Kunming Medical University & Yunnan Key Laboratory of Stem Cell and Regenerative Medicine, Kunming Medical University, Kunming, Yunnan 650032, China; Scientific Research Laboratory Center, First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan 650032, China
| | - Yu Zhao
- NHC Key Laboratory of Drug Addiction Medicine, First Affiliated Hospital of Kunming Medical University & Yunnan Key Laboratory of Stem Cell and Regenerative Medicine, Kunming Medical University, Kunming, Yunnan 650032, China; Scientific Research Laboratory Center, First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan 650032, China
| | - Jian-Hua Wang
- Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, Guangdong 510530, China.
| | - Yi-Qun Kuang
- NHC Key Laboratory of Drug Addiction Medicine, First Affiliated Hospital of Kunming Medical University & Yunnan Key Laboratory of Stem Cell and Regenerative Medicine, Kunming Medical University, Kunming, Yunnan 650032, China; Scientific Research Laboratory Center, First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan 650032, China.
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Wei Y, Hong Y, Yang L, Wang J, Zhao T, Zheng X, Kang L, Chen J, Han L, Long C, Shen L, Wu S, Wei G. Single-cell transcriptomic dissection of the toxic impact of di(2-ethylhexyl) phthalate on immature testicular development at the neonatal stage. Food Chem Toxicol 2023; 176:113780. [PMID: 37059381 DOI: 10.1016/j.fct.2023.113780] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2023] [Revised: 03/29/2023] [Accepted: 04/11/2023] [Indexed: 04/16/2023]
Abstract
Di(2-ethylhexyl) phthalate (DEHP) early exposure leads to immature testicular injury, and we aimed to utilize single-cell RNA (scRNA) sequencing to comprehensively assess the toxic effect of DEHP on testicular development. Therefore, we gavaged pregnant C57BL/6 mice with 750 mg/kg body weight DEHP from gestational day 13.5 to delivery and performed scRNA sequencing of neonatal testes at postnatal day 5.5. The results revealed the gene expression dynamics in testicular cells. DEHP disrupted the developmental trajectory of germ cells and the balance between the self-renewal and differentiation of spermatogonial stem cells. Additionally, DEHP caused an abnormal developmental trajectory, cytoskeletal damage and cell cycle arrest in Sertoli cells; disrupted the metabolism of testosterone in Leydig cells; and disturbed the developmental trajectory in peritubular myoid cells. Elevated oxidative stress and excessive apoptosis mediated by p53 were observed in almost all testicular cells. The intercellular interactions among four cell types were altered, and biological processes related to glial cell line-derived neurotrophic factor (GDNF), transforming growth factor-β (TGF-β), NOTCH, platelet-derived growth factor (PDGF) and WNT signaling pathways were enriched after DEHP treatment. These findings systematically describe the damaging effects of DEHP on the immature testes and provide substantial novel insights into the reproductive toxicity of DEHP.
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Affiliation(s)
- Yuexin Wei
- Department of Urology, Children's Hospital of Chongqing Medical University, Chongqing, 400014, PR China; Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing Key Laboratory of Pediatrics, Ministry of Education Key Laboratory of Child Development and Disorders, National Clinical Research Center for Child Health and Disorders, China International Science and Technology Cooperation base of Child development and Critical Disorders, Children's Hospital of Chongqing Medical University, Chongqing, 400014, PR China
| | - Yifan Hong
- Department of Urology, Children's Hospital of Chongqing Medical University, Chongqing, 400014, PR China; Pediatric Research Institute, Children's Hospital of Chongqing Medical University, Chongqing, 400014, PR China; Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing Key Laboratory of Pediatrics, Ministry of Education Key Laboratory of Child Development and Disorders, National Clinical Research Center for Child Health and Disorders, China International Science and Technology Cooperation base of Child development and Critical Disorders, Children's Hospital of Chongqing Medical University, Chongqing, 400014, PR China
| | - Liuqing Yang
- Pediatric Research Institute, Children's Hospital of Chongqing Medical University, Chongqing, 400014, PR China; Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing Key Laboratory of Pediatrics, Ministry of Education Key Laboratory of Child Development and Disorders, National Clinical Research Center for Child Health and Disorders, China International Science and Technology Cooperation base of Child development and Critical Disorders, Children's Hospital of Chongqing Medical University, Chongqing, 400014, PR China
| | - Junke Wang
- Department of Urology, Children's Hospital of Chongqing Medical University, Chongqing, 400014, PR China; Pediatric Research Institute, Children's Hospital of Chongqing Medical University, Chongqing, 400014, PR China; Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing Key Laboratory of Pediatrics, Ministry of Education Key Laboratory of Child Development and Disorders, National Clinical Research Center for Child Health and Disorders, China International Science and Technology Cooperation base of Child development and Critical Disorders, Children's Hospital of Chongqing Medical University, Chongqing, 400014, PR China
| | - Tianxin Zhao
- Department of Urology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangdong Provincial Clinical Research Center for Child Health, Guangzhou, 510623, PR China
| | - Xiangqin Zheng
- Department of Urology, Children's Hospital of Chongqing Medical University, Chongqing, 400014, PR China; Pediatric Research Institute, Children's Hospital of Chongqing Medical University, Chongqing, 400014, PR China; Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing Key Laboratory of Pediatrics, Ministry of Education Key Laboratory of Child Development and Disorders, National Clinical Research Center for Child Health and Disorders, China International Science and Technology Cooperation base of Child development and Critical Disorders, Children's Hospital of Chongqing Medical University, Chongqing, 400014, PR China
| | - Lian Kang
- Department of Urology, Children's Hospital of Chongqing Medical University, Chongqing, 400014, PR China; Pediatric Research Institute, Children's Hospital of Chongqing Medical University, Chongqing, 400014, PR China; Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing Key Laboratory of Pediatrics, Ministry of Education Key Laboratory of Child Development and Disorders, National Clinical Research Center for Child Health and Disorders, China International Science and Technology Cooperation base of Child development and Critical Disorders, Children's Hospital of Chongqing Medical University, Chongqing, 400014, PR China
| | - Jiadong Chen
- Department of Urology, Children's Hospital of Chongqing Medical University, Chongqing, 400014, PR China; Pediatric Research Institute, Children's Hospital of Chongqing Medical University, Chongqing, 400014, PR China; Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing Key Laboratory of Pediatrics, Ministry of Education Key Laboratory of Child Development and Disorders, National Clinical Research Center for Child Health and Disorders, China International Science and Technology Cooperation base of Child development and Critical Disorders, Children's Hospital of Chongqing Medical University, Chongqing, 400014, PR China
| | - Lindong Han
- Department of Urology, Children's Hospital of Chongqing Medical University, Chongqing, 400014, PR China; Pediatric Research Institute, Children's Hospital of Chongqing Medical University, Chongqing, 400014, PR China; Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing Key Laboratory of Pediatrics, Ministry of Education Key Laboratory of Child Development and Disorders, National Clinical Research Center for Child Health and Disorders, China International Science and Technology Cooperation base of Child development and Critical Disorders, Children's Hospital of Chongqing Medical University, Chongqing, 400014, PR China
| | - Chunlan Long
- Pediatric Research Institute, Children's Hospital of Chongqing Medical University, Chongqing, 400014, PR China; Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing Key Laboratory of Pediatrics, Ministry of Education Key Laboratory of Child Development and Disorders, National Clinical Research Center for Child Health and Disorders, China International Science and Technology Cooperation base of Child development and Critical Disorders, Children's Hospital of Chongqing Medical University, Chongqing, 400014, PR China
| | - Lianju Shen
- Pediatric Research Institute, Children's Hospital of Chongqing Medical University, Chongqing, 400014, PR China; Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing Key Laboratory of Pediatrics, Ministry of Education Key Laboratory of Child Development and Disorders, National Clinical Research Center for Child Health and Disorders, China International Science and Technology Cooperation base of Child development and Critical Disorders, Children's Hospital of Chongqing Medical University, Chongqing, 400014, PR China
| | - Shengde Wu
- Department of Urology, Children's Hospital of Chongqing Medical University, Chongqing, 400014, PR China; Pediatric Research Institute, Children's Hospital of Chongqing Medical University, Chongqing, 400014, PR China; Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing Key Laboratory of Pediatrics, Ministry of Education Key Laboratory of Child Development and Disorders, National Clinical Research Center for Child Health and Disorders, China International Science and Technology Cooperation base of Child development and Critical Disorders, Children's Hospital of Chongqing Medical University, Chongqing, 400014, PR China.
| | - Guanghui Wei
- Department of Urology, Children's Hospital of Chongqing Medical University, Chongqing, 400014, PR China; Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing Key Laboratory of Pediatrics, Ministry of Education Key Laboratory of Child Development and Disorders, National Clinical Research Center for Child Health and Disorders, China International Science and Technology Cooperation base of Child development and Critical Disorders, Children's Hospital of Chongqing Medical University, Chongqing, 400014, PR China
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Magenheim J, Maestro MA, Sharon N, Herrera PL, Murtaugh LC, Kopp J, Sander M, Gu G, Melton DA, Ferrer J, Dor Y. Matters arising: Insufficient evidence that pancreatic β cells are derived from adult ductal Neurog3-expressing progenitors. Cell Stem Cell 2023; 30:488-497.e3. [PMID: 37028408 DOI: 10.1016/j.stem.2023.03.003] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Revised: 05/29/2022] [Accepted: 03/01/2023] [Indexed: 04/08/2023]
Abstract
Understanding the origin of pancreatic β cells has profound implications for regenerative therapies in diabetes. For over a century, it was widely held that adult pancreatic duct cells act as endocrine progenitors, but lineage-tracing experiments challenged this dogma. Gribben et al. recently used two existing lineage-tracing models and single-cell RNA sequencing to conclude that adult pancreatic ducts contain endocrine progenitors that differentiate to insulin-expressing β cells at a physiologically important rate. We now offer an alternative interpretation of these experiments. Our data indicate that the two Cre lines that were used directly label adult islet somatostatin-producing ∂ cells, which precludes their use to assess whether β cells originate from duct cells. Furthermore, many labeled ∂ cells, which have an elongated neuron-like shape, were likely misclassified as β cells because insulin-somatostatin coimmunolocalizations were not used. We conclude that most evidence so far indicates that endocrine and exocrine lineage borders are rarely crossed in the adult pancreas.
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Nguyen HCT, Baik B, Yoon S, Park T, Nam D. Benchmarking integration of single-cell differential expression. Nat Commun 2023; 14:1570. [PMID: 36944632 PMCID: PMC10030080 DOI: 10.1038/s41467-023-37126-3] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 03/03/2023] [Indexed: 03/23/2023] Open
Abstract
Integration of single-cell RNA sequencing data between different samples has been a major challenge for analyzing cell populations. However, strategies to integrate differential expression analysis of single-cell data remain underinvestigated. Here, we benchmark 46 workflows for differential expression analysis of single-cell data with multiple batches. We show that batch effects, sequencing depth and data sparsity substantially impact their performances. Notably, we find that the use of batch-corrected data rarely improves the analysis for sparse data, whereas batch covariate modeling improves the analysis for substantial batch effects. We show that for low depth data, single-cell techniques based on zero-inflation model deteriorate the performance, whereas the analysis of uncorrected data using limmatrend, Wilcoxon test and fixed effects model performs well. We suggest several high-performance methods under different conditions based on various simulation and real data analyses. Additionally, we demonstrate that differential expression analysis for a specific cell type outperforms that of large-scale bulk sample data in prioritizing disease-related genes.
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Affiliation(s)
- Hai C T Nguyen
- Department of Biological Sciences, Ulsan National Institute of Science and Technology, Ulsan, 44919, Republic of Korea
| | - Bukyung Baik
- Department of Biological Sciences, Ulsan National Institute of Science and Technology, Ulsan, 44919, Republic of Korea
| | - Sora Yoon
- Department of Biological Sciences, Ulsan National Institute of Science and Technology, Ulsan, 44919, Republic of Korea
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Taesung Park
- Department of Statistics, Seoul National University, Seoul, 08826, Republic of Korea
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, 08826, Republic of Korea
| | - Dougu Nam
- Department of Biological Sciences, Ulsan National Institute of Science and Technology, Ulsan, 44919, Republic of Korea.
- Department of Mathematical Sciences, Ulsan National Institute of Science and Technology, Ulsan, 44919, Republic of Korea.
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Wang X, Liu Q, Li J, Zhou L, Wang T, Zhao N. Dynamic cellular and molecular characteristics of spermatogenesis in the viviparous marine teleost Sebastes schlegelii†. Biol Reprod 2023; 108:338-352. [PMID: 36401879 DOI: 10.1093/biolre/ioac203] [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: 03/05/2022] [Revised: 07/13/2022] [Accepted: 11/02/2022] [Indexed: 11/21/2022] Open
Abstract
Spermatogenesis is a dynamic cell developmental process that is essential for reproductive success. Vertebrates utilize a variety of reproductive strategies, including sperm diversity, and internal and external fertilization. Research on the cellular and molecular dynamic changes involved in viviparous teleost spermatogenesis, however, is currently lacking. Here, we combined cytohistology, 10 × genomic single-cell RNA-seq, and transcriptome technology to determine the dynamic development characteristics of the spermatogenesis of Sebastes schlegelii. The expressions of lhcgr (Luteinizing hormone/Choriogonadotropin receptor), fshr (follicle-stimulating hormone receptor), ar (androgen receptor), pgr (progesterone receptor), and cox (cyclo-oxygen-ase), as well as the prostaglandin E and F levels peaked during the maturation period, indicating that they were important for sperm maturation and mating. Fifteen clusters were identified based on the 10 × genomic single-cell results. The cell markers of the sub-cluster were identified by their upregulation; piwil, dazl, and dmrt1 were upregulated and identified as spermatogonium markers, and sycp1/3 and spo11 were identified as spermatocyte markers. For S. schlegelii, the sperm head nucleus was elongated (spherical to streamlined in shape), which is a typical characteristic for sperm involved in internal fertilization. We also identified a series of crucial genes associated with spermiogenesis, such as spata6, spag16, kif20a, trip10, and klf10, while kif2c, kifap3, fez2, and spaca6 were found to be involved in nucleus elongation. The results of this study will enrich our cellular and molecular knowledge of spermatogenesis and spermiogenesis in fish that undergo internal fertilization.
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Affiliation(s)
- Xueying Wang
- CAS and Shandong Province Key Laboratory of Experimental Marine Biology, Center for Ocean Mega-Science, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China.,Laboratory for Marine Biology and Biotechnology, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China
| | - Qinghua Liu
- CAS and Shandong Province Key Laboratory of Experimental Marine Biology, Center for Ocean Mega-Science, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China.,Laboratory for Marine Biology and Biotechnology, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China
| | - Jun Li
- CAS and Shandong Province Key Laboratory of Experimental Marine Biology, Center for Ocean Mega-Science, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China.,Laboratory for Marine Biology and Biotechnology, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China
| | - Li Zhou
- CAS and Shandong Province Key Laboratory of Experimental Marine Biology, Center for Ocean Mega-Science, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China.,Laboratory for Marine Biology and Biotechnology, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China.,College of Marine Science, University of Chinese Academy of Sciences, Beijing, China
| | - Tao Wang
- CAS and Shandong Province Key Laboratory of Experimental Marine Biology, Center for Ocean Mega-Science, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China.,Laboratory for Marine Biology and Biotechnology, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China.,School of Marine Science and Engineering, Qingdao Agricultural University, Qingdao, China
| | - Ning Zhao
- CAS and Shandong Province Key Laboratory of Experimental Marine Biology, Center for Ocean Mega-Science, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China.,Laboratory for Marine Biology and Biotechnology, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China.,College of Marine Science, University of Chinese Academy of Sciences, Beijing, China
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Danielli SG, Porpiglia E, De Micheli AJ, Navarro N, Zellinger MJ, Bechtold I, Kisele S, Volken L, Marques JG, Kasper S, Bode PK, Henssen AG, Gürgen D, Delattre O, Surdez D, Roma J, Bühlmann P, Blau HM, Wachtel M, Schäfer BW. Single-cell profiling of alveolar rhabdomyosarcoma reveals RAS pathway inhibitors as cell-fate hijackers with therapeutic relevance. SCIENCE ADVANCES 2023; 9:eade9238. [PMID: 36753540 PMCID: PMC9908029 DOI: 10.1126/sciadv.ade9238] [Citation(s) in RCA: 33] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/09/2023]
Abstract
Rhabdomyosarcoma (RMS) is a group of pediatric cancers with features of developing skeletal muscle. The cellular hierarchy and mechanisms leading to developmental arrest remain elusive. Here, we combined single-cell RNA sequencing, mass cytometry, and high-content imaging to resolve intratumoral heterogeneity of patient-derived primary RMS cultures. We show that the aggressive alveolar RMS (aRMS) subtype contains plastic muscle stem-like cells and cycling progenitors that drive tumor growth, and a subpopulation of differentiated cells that lost its proliferative potential and correlates with better outcomes. While chemotherapy eliminates cycling progenitors, it enriches aRMS for muscle stem-like cells. We screened for drugs hijacking aRMS toward clinically favorable subpopulations and identified a combination of RAF and MEK inhibitors that potently induces myogenic differentiation and inhibits tumor growth. Overall, our work provides insights into the developmental states underlying aRMS aggressiveness, chemoresistance, and progression and identifies the RAS pathway as a promising therapeutic target.
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Affiliation(s)
- Sara G. Danielli
- Department of Oncology and Children’s Research Center, University Children’s Hospital of Zurich, Zürich 8032, Switzerland
| | - Ermelinda Porpiglia
- Baxter Laboratory for Stem Cell Biology, Department of Microbiology and Immunology, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
- Department of Biomedicine, Aarhus University, Aarhus C 8000, Denmark
- Corresponding author. (B.W.S.); (M.W.); (E.P.)
| | - Andrea J. De Micheli
- Department of Oncology and Children’s Research Center, University Children’s Hospital of Zurich, Zürich 8032, Switzerland
| | - Natalia Navarro
- Laboratory of Translational Research in Child and Adolescent Cancer, Vall d’Hebron Research Institute, Hospital Universitari Vall d’Hebron, Universitat Autònoma de Barcelona, Barcelona 08035, Spain
| | | | - Ingrid Bechtold
- Department of Oncology and Children’s Research Center, University Children’s Hospital of Zurich, Zürich 8032, Switzerland
| | - Samanta Kisele
- Department of Oncology and Children’s Research Center, University Children’s Hospital of Zurich, Zürich 8032, Switzerland
| | - Larissa Volken
- Department of Oncology and Children’s Research Center, University Children’s Hospital of Zurich, Zürich 8032, Switzerland
| | - Joana G. Marques
- Department of Oncology and Children’s Research Center, University Children’s Hospital of Zurich, Zürich 8032, Switzerland
| | - Stephanie Kasper
- Department of Oncology and Children’s Research Center, University Children’s Hospital of Zurich, Zürich 8032, Switzerland
| | - Peter K. Bode
- Department of Pathology, University Hospital Zurich, Zurich, Switzerland
| | - Anton G. Henssen
- Department of Pediatric Oncology/Hematology, Charité–Universitätsmedizin Berlin, Berlin 13353, Germany
| | - Dennis Gürgen
- EPO Experimental Pharmacology and Oncology Berlin-Buch GmbH Berlin 13125, Germany
| | - Olivier Delattre
- INSERM U830, Équipe Labellisée LNCC, Diversity and Plasticity of Childhood Tumors Laboratory, PSL Research University, SIREDO Oncology Center, Institut Curie Research Center, Paris 75005, France
| | - Didier Surdez
- INSERM U830, Équipe Labellisée LNCC, Diversity and Plasticity of Childhood Tumors Laboratory, PSL Research University, SIREDO Oncology Center, Institut Curie Research Center, Paris 75005, France
- Balgrist University Hospital, Faculty of Medicine, University of Zurich (UZH), Zurich, Switzerland
| | - Josep Roma
- Laboratory of Translational Research in Child and Adolescent Cancer, Vall d’Hebron Research Institute, Hospital Universitari Vall d’Hebron, Universitat Autònoma de Barcelona, Barcelona 08035, Spain
| | - Peter Bühlmann
- Seminar for Statistics, ETH Zürich, Zürich 8092, Switzerland
| | - Helen M. Blau
- Baxter Laboratory for Stem Cell Biology, Department of Microbiology and Immunology, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Marco Wachtel
- Department of Oncology and Children’s Research Center, University Children’s Hospital of Zurich, Zürich 8032, Switzerland
- Corresponding author. (B.W.S.); (M.W.); (E.P.)
| | - Beat W. Schäfer
- Department of Oncology and Children’s Research Center, University Children’s Hospital of Zurich, Zürich 8032, Switzerland
- Corresponding author. (B.W.S.); (M.W.); (E.P.)
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48
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Dousti Mousavi N, Yang J, Aldirawi H. Variable Selection for Sparse Data with Applications to Vaginal Microbiome and Gene Expression Data. Genes (Basel) 2023; 14:403. [PMID: 36833330 PMCID: PMC9956208 DOI: 10.3390/genes14020403] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Revised: 01/19/2023] [Accepted: 01/31/2023] [Indexed: 02/09/2023] Open
Abstract
Sparse data with a high portion of zeros arise in various disciplines. Modeling sparse high-dimensional data is a challenging and growing research area. In this paper, we provide statistical methods and tools for analyzing sparse data in a fairly general and complex context. We utilize two real scientific applications as illustrations, including a longitudinal vaginal microbiome data and a high dimensional gene expression data. We recommend zero-inflated model selections and significance tests to identify the time intervals when the pregnant and non-pregnant groups of women are significantly different in terms of Lactobacillus species. We apply the same techniques to select the best 50 genes out of 2426 sparse gene expression data. The classification based on our selected genes achieves 100% prediction accuracy. Furthermore, the first four principal components based on the selected genes can explain as high as 83% of the model variability.
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Affiliation(s)
- Niloufar Dousti Mousavi
- Department of Mathematics, Statistics, and Computer Science, University of Illinois at Chicago, Chicago, IL 60607, USA
| | - Jie Yang
- Department of Mathematics, Statistics, and Computer Science, University of Illinois at Chicago, Chicago, IL 60607, USA
| | - Hani Aldirawi
- Department of Mathematics, California State University—San Bernardino, San Bernardino, CA 92407, USA
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Piekna-Przybylska D, Na D, Zhang J, Baker C, Ashton JM, White PM. Single cell RNA sequencing analysis of mouse cochlear supporting cell transcriptomes with activated ERBB2 receptor indicates a cell-specific response that promotes CD44 activation. Front Cell Neurosci 2023; 16:1096872. [PMID: 36687526 PMCID: PMC9853549 DOI: 10.3389/fncel.2022.1096872] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2022] [Accepted: 12/12/2022] [Indexed: 01/07/2023] Open
Abstract
Hearing loss caused by the death of cochlear hair cells (HCs) might be restored through regeneration from supporting cells (SCs) via dedifferentiation and proliferation, as observed in birds. In a previous report, ERBB2 activation in a subset of cochlear SCs promoted widespread down-regulation of SOX2 in neighboring cells, proliferation, and the differentiation of HC-like cells. Here we analyze single cell transcriptomes from neonatal mouse cochlear SCs with activated ERBB2, with the goal of identifying potential secreted effectors. ERBB2 induction in vivo generated a new population of cells with de novo expression of a gene network. Called small integrin-binding ligand n-linked glycoproteins (SIBLINGs), these ligands and their regulators can alter NOTCH signaling and promote cell survival, proliferation, and differentiation in other systems. We validated mRNA expression of network members, and then extended our analysis to older stages. ERBB2 signaling in young adult SCs also promoted protein expression of gene network members. Furthermore, we found proliferating cochlear cell aggregates in the organ of Corti. Our results suggest that ectopic activation of ERBB2 signaling in cochlear SCs can alter the microenvironment, promoting proliferation and cell rearrangements. Together these results suggest a novel mechanism for inducing stem cell-like activity in the adult mammalian cochlea.
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Affiliation(s)
- Dorota Piekna-Przybylska
- Department of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, NY, United States
| | - Daxiang Na
- Department of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, NY, United States
| | - Jingyuan Zhang
- Department of Biology, University of Rochester, Rochester, NY, United States
| | - Cameron Baker
- Genomic Research Center, University of Rochester School of Medicine and Dentistry, Rochester, NY, United States
| | - John M. Ashton
- Genomic Research Center, University of Rochester School of Medicine and Dentistry, Rochester, NY, United States
| | - Patricia M. White
- Department of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, NY, United States
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50
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Cheema AS, Duan K, Dalod M, Vu Manh TP. Harnessing Single-Cell RNA Sequencing to Identify Dendritic Cell Types, Characterize Their Biological States, and Infer Their Activation Trajectory. Methods Mol Biol 2023; 2618:319-373. [PMID: 36905526 DOI: 10.1007/978-1-0716-2938-3_22] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/12/2023]
Abstract
Dendritic cells (DCs) orchestrate innate and adaptive immunity, by translating the sensing of distinct danger signals into the induction of different effector lymphocyte responses, to induce the defense mechanisms the best suited to face the threat. Hence, DCs are very plastic, which results from two key characteristics. First, DCs encompass distinct cell types specialized in different functions. Second, each DC type can undergo different activation states, fine-tuning its functions depending on its tissue microenvironment and the pathophysiological context, by adapting the output signals it delivers to the input signals it receives. Hence, to better understand DC biology and harness it in the clinic, we must determine which combinations of DC types and activation states mediate which functions and how.To decipher the nature, functions, and regulation of DC types and their physiological activation states, one of the methods that can be harnessed most successfully is ex vivo single-cell RNA sequencing (scRNAseq). However, for new users of this approach, determining which analytics strategy and computational tools to choose can be quite challenging, considering the rapid evolution and broad burgeoning in the field. In addition, awareness must be raised on the need for specific, robust, and tractable strategies to annotate cells for cell type identity and activation states. It is also important to emphasize the necessity of examining whether similar cell activation trajectories are inferred by using different, complementary methods. In this chapter, we take these issues into account for providing a pipeline for scRNAseq analysis and illustrating it with a tutorial reanalyzing a public dataset of mononuclear phagocytes isolated from the lungs of naïve or tumor-bearing mice. We describe this pipeline step-by-step, including data quality controls, dimensionality reduction, cell clustering, cell cluster annotation, inference of the cell activation trajectories, and investigation of the underpinning molecular regulation. It is accompanied with a more complete tutorial on GitHub. We hope that this method will be helpful for both wet lab and bioinformatics researchers interested in harnessing scRNAseq data for deciphering the biology of DCs or other cell types and that it will contribute to establishing high standards in the field.
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Affiliation(s)
- Ammar Sabir Cheema
- Aix Marseille Univ, CNRS, INSERM, CIML, Centre d'Immunologie de Marseille-Luminy, Turing Center for Living Systems, Marseille, France
| | - Kaibo Duan
- Singapore Immunology Network, Agency for Science, Technology and Research, 8A Biomedical Grove, Singapore 138648, Singapore
| | - Marc Dalod
- Aix Marseille Univ, CNRS, INSERM, CIML, Centre d'Immunologie de Marseille-Luminy, Turing Center for Living Systems, Marseille, France.
| | - Thien-Phong Vu Manh
- Aix Marseille Univ, CNRS, INSERM, CIML, Centre d'Immunologie de Marseille-Luminy, Turing Center for Living Systems, Marseille, France.
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