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Volteras D, Shahrezaei V, Thomas P. Global transcription regulation revealed from dynamical correlations in time-resolved single-cell RNA sequencing. Cell Syst 2024; 15:694-708.e12. [PMID: 39121860 DOI: 10.1016/j.cels.2024.07.002] [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: 10/24/2023] [Revised: 02/29/2024] [Accepted: 07/11/2024] [Indexed: 08/12/2024]
Abstract
Single-cell transcriptomics reveals significant variations in transcriptional activity across cells. Yet, it remains challenging to identify mechanisms of transcription dynamics from static snapshots. It is thus still unknown what drives global transcription dynamics in single cells. We present a stochastic model of gene expression with cell size- and cell cycle-dependent rates in growing and dividing cells that harnesses temporal dimensions of single-cell RNA sequencing through metabolic labeling protocols and cel lcycle reporters. We develop a parallel and highly scalable approximate Bayesian computation method that corrects for technical variation and accurately quantifies absolute burst frequency, burst size, and degradation rate along the cell cycle at a transcriptome-wide scale. Using Bayesian model selection, we reveal scaling between transcription rates and cell size and unveil waves of gene regulation across the cell cycle-dependent transcriptome. Our study shows that stochastic modeling of dynamical correlations identifies global mechanisms of transcription regulation. A record of this paper's transparent peer review process is included in the supplemental information.
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Affiliation(s)
- Dimitris Volteras
- Department of Mathematics, Faculty of Natural Sciences, Imperial College London, London, SW7 2AZ, UK
| | - Vahid Shahrezaei
- Department of Mathematics, Faculty of Natural Sciences, Imperial College London, London, SW7 2AZ, UK.
| | - Philipp Thomas
- Department of Mathematics, Faculty of Natural Sciences, Imperial College London, London, SW7 2AZ, UK.
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Park HS, Bang JH, Jung WH, Yang JY, Shin HJ, Son JH, Han JW, Lee SH, Chung KH, Kim K, Chang HS, Park TK. Development of Non-Invasive miRNA Markers for Assessing the Quality of Human Induced Pluripotent Stem Cell-Derived Retinal Organoids. Int J Mol Sci 2024; 25:8011. [PMID: 39125582 PMCID: PMC11312389 DOI: 10.3390/ijms25158011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2024] [Revised: 07/17/2024] [Accepted: 07/18/2024] [Indexed: 08/12/2024] Open
Abstract
Human retinal organoids (ROs) have emerged as valuable tools for studying retinal development, modeling human retinal diseases, and screening drugs. However, their application is limited primarily due to time-intensive generation, high costs, and low reproducibility. Quality assessment of RO differentiation is crucial for their application in research. However, traditional methods such as morphological evaluation and immunohistochemical analysis have limitations due to their lack of precision and invasiveness, respectively. This study aims to identify non-invasive biomarkers for RO differentiation quality using exosomal microRNAs (miRNAs), which are known to reflect cell-specific functions and development in the retina. We differentiated ROs from human induced pluripotent stem cells (hiPSCs) and classified them into 'superior' and 'inferior' groups based on morphological and immunohistochemical criteria. Exosomes from the conditioned media were isolated and analyzed for miRNA content. Our findings revealed distinct miRNA profiles between superior and inferior ROs, with superior ROs exhibiting higher miRNA diversity and specifically up- or down-regulated miRNAs. Gene ontology and pathway enrichment analyses indicated that the target genes of these miRNAs are involved in neuron proliferation and differentiation. The study suggests the potential of exosomal hsa-miR-654-3p and hsa-miR-451a as non-invasive biomarkers for real-time monitoring of RO quality, facilitating the development of standardized, efficient, and cost-effective culture methods.
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Affiliation(s)
- Hyo Song Park
- Divisions of Ophthalmology, Soonchunhyang University Bucheon Hospital, College of Medicine, Soonchunhyang University, Bucheon 14584, Republic of Korea; (H.S.P.); (W.H.J.); (J.W.H.); (S.H.L.)
| | - Ji-Hong Bang
- Department of Interdisciplinary Program in Biomedical Science Major, Graduate School, Soonchunhyang University, Asan 31538, Republic of Korea; (J.-H.B.); (H.J.S.)
| | - Wook Hyun Jung
- Divisions of Ophthalmology, Soonchunhyang University Bucheon Hospital, College of Medicine, Soonchunhyang University, Bucheon 14584, Republic of Korea; (H.S.P.); (W.H.J.); (J.W.H.); (S.H.L.)
| | - Jin Young Yang
- Laboratory of Molecular Therapy for Retinal Degeneration, Soonchunhyang University Bucheon Hospital, Bucheon 31538, Republic of Korea; (J.Y.Y.); (K.H.C.)
| | - Hee Jeong Shin
- Department of Interdisciplinary Program in Biomedical Science Major, Graduate School, Soonchunhyang University, Asan 31538, Republic of Korea; (J.-H.B.); (H.J.S.)
- Laboratory of Molecular Therapy for Retinal Degeneration, Soonchunhyang University Bucheon Hospital, Bucheon 31538, Republic of Korea; (J.Y.Y.); (K.H.C.)
| | - Ji-Hye Son
- Department of Microbiology, College of Medicine, Soonchunhyang University, Cheonan 33151, Republic of Korea;
| | - Jung Woo Han
- Divisions of Ophthalmology, Soonchunhyang University Bucheon Hospital, College of Medicine, Soonchunhyang University, Bucheon 14584, Republic of Korea; (H.S.P.); (W.H.J.); (J.W.H.); (S.H.L.)
| | - Si Hyung Lee
- Divisions of Ophthalmology, Soonchunhyang University Bucheon Hospital, College of Medicine, Soonchunhyang University, Bucheon 14584, Republic of Korea; (H.S.P.); (W.H.J.); (J.W.H.); (S.H.L.)
| | - Kyung Hwun Chung
- Laboratory of Molecular Therapy for Retinal Degeneration, Soonchunhyang University Bucheon Hospital, Bucheon 31538, Republic of Korea; (J.Y.Y.); (K.H.C.)
| | - Kyunggon Kim
- Department of Digital Medicine, Brain Korea 21 plus, College of Medicine, University of Ulsan and Asan Medical Center, Seoul 05505, Republic of Korea;
| | - Hun Soo Chang
- Department of Interdisciplinary Program in Biomedical Science Major, Graduate School, Soonchunhyang University, Asan 31538, Republic of Korea; (J.-H.B.); (H.J.S.)
- Department of Microbiology, College of Medicine, Soonchunhyang University, Cheonan 33151, Republic of Korea;
| | - Tae Kwann Park
- Divisions of Ophthalmology, Soonchunhyang University Bucheon Hospital, College of Medicine, Soonchunhyang University, Bucheon 14584, Republic of Korea; (H.S.P.); (W.H.J.); (J.W.H.); (S.H.L.)
- Department of Interdisciplinary Program in Biomedical Science Major, Graduate School, Soonchunhyang University, Asan 31538, Republic of Korea; (J.-H.B.); (H.J.S.)
- Laboratory of Molecular Therapy for Retinal Degeneration, Soonchunhyang University Bucheon Hospital, Bucheon 31538, Republic of Korea; (J.Y.Y.); (K.H.C.)
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Maizels RJ, Snell DM, Briscoe J. Reconstructing developmental trajectories using latent dynamical systems and time-resolved transcriptomics. Cell Syst 2024; 15:411-424.e9. [PMID: 38754365 DOI: 10.1016/j.cels.2024.04.004] [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: 09/19/2023] [Revised: 02/01/2024] [Accepted: 04/17/2024] [Indexed: 05/18/2024]
Abstract
The snapshot nature of single-cell transcriptomics presents a challenge for studying the dynamics of cell fate decisions. Metabolic labeling and splicing can provide temporal information at single-cell level, but current methods have limitations. Here, we present a framework that overcomes these limitations: experimentally, we developed sci-FATE2, an optimized method for metabolic labeling with increased data quality, which we used to profile 45,000 embryonic stem (ES) cells differentiating into neural tube identities. Computationally, we developed a two-stage framework for dynamical modeling: VelvetVAE, a variational autoencoder (VAE) for velocity inference that outperforms all other tools tested, and VelvetSDE, a neural stochastic differential equation (nSDE) framework for simulating trajectory distributions. These recapitulate underlying dataset distributions and capture features such as decision boundaries between alternative fates and fate-specific gene expression. These methods recast single-cell analyses from descriptions of observed data to models of the dynamics that generated them, providing a framework for investigating developmental fate decisions.
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Affiliation(s)
- Rory J Maizels
- The Francis Crick Institute, 1 Midland Road, London NW1 1AT, UK; University College, London, UK
| | - Daniel M Snell
- The Francis Crick Institute, 1 Midland Road, London NW1 1AT, UK
| | - James Briscoe
- The Francis Crick Institute, 1 Midland Road, London NW1 1AT, UK.
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Maizels RJ. A dynamical perspective: moving towards mechanism in single-cell transcriptomics. Philos Trans R Soc Lond B Biol Sci 2024; 379:20230049. [PMID: 38432314 PMCID: PMC10909508 DOI: 10.1098/rstb.2023.0049] [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: 07/10/2023] [Accepted: 10/31/2023] [Indexed: 03/05/2024] Open
Abstract
As the field of single-cell transcriptomics matures, research is shifting focus from phenomenological descriptions of cellular phenotypes to a mechanistic understanding of the gene regulation underneath. This perspective considers the value of capturing dynamical information at single-cell resolution for gaining mechanistic insight; reviews the available technologies for recording and inferring temporal information in single cells; and explores whether better dynamical resolution is sufficient to adequately capture the causal relationships driving complex biological systems. This article is part of a discussion meeting issue 'Causes and consequences of stochastic processes in development and disease'.
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Affiliation(s)
- Rory J. Maizels
- The Francis Crick Institute, 1 Midland Road, London NW1 1AT, UK
- University College London, London WC1E 6BT, UK
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Wyler E. Single-Cell RNA-Sequencing of RVFV Infection. Methods Mol Biol 2024; 2824:361-372. [PMID: 39039423 DOI: 10.1007/978-1-0716-3926-9_22] [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: 07/24/2024]
Abstract
On the RNA level, viral infections are characterized by perturbations in the host cell transcriptome as well as the development of viral genetic information. Investigating the abundance and dynamic of RNA molecules can provide ample information to understand many aspects of the infection, from viral replication to pathogenesis. A key aspect therein is the resolution of the data, as infections are generally highly heterogeneous. Even in simple model systems such as cell lines, viral infections happen in a very asynchronous way. Quantifying RNAs at single-cell resolution can therefore substantially increase our understanding of these processes.Whereas measuring the RNA in bulk, that is, in samples containing thousands to hundreds of thousands of cells, is established and widely used since many years, methods for studying not only just a few different RNAs in individual cells became widely available only recently. Here, I outline and compare current concepts and methodologies for using single-cell RNA-sequencing to study virus infections. This covers sample preparation, cell preservation, biosafety considerations, and various experimental methods, with a special focus on the aspects that are important for studying virus infections. Since there is not "the one" method for doing single-cell RNA-sequencing, I will not provide a detailed protocol. Rather, this chapter should serve as a primer for getting started with single-cell RNA-sequencing experiments of virus infections and discusses the criteria that allow readers to choose the best procedures for their specific research question.
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Affiliation(s)
- Emanuel Wyler
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine, Helmholtz Association, Berlin, Germany.
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