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      Identifying a Lung Stem Cell Subpopulation by Combining Single-Cell Morphometrics, Organoid Culture, and Transcriptomics

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          Abstract

          Single-cell RNA sequencing is a valuable tool for dissecting cellular heterogeneity in complex systems. However, it is still challenging to estimate the proliferation and differentiation potentials of subpopulations within dormant tissue stem cells. Here, we established a new single-cell analysis method for profiling the organoid-forming capacity and differentiation potential of tissue stem cells to disclose stem cell subpopulations by integrating single-cell morphometrics, organoid-forming assay, and RNA sequencing, a method named scMORN. To explore lung epithelial stem cells, we initially developed feeder-free culture system, which could expand all major lung stem cells, including basal, club, and alveolar type 2 (AT2) cells, and found that club cells contained a subpopulation, which showed better survival rate and high proliferation capacity and could differentiate into alveolar cells. Using the scMORN method, we discovered a club cell subpopulation named Muc5b + and large club (ML-club) cells that efficiently formed organoids than other club or AT2 cells in our feeder-free organoid culture and differentiated into alveolar cells in vitro. Single-cell transcriptome profiling and immunohistochemical analysis revealed that ML-club cells localized at the intrapulmonary proximal airway and distinct from known subpopulations of club cells such as BASCs. Furthermore, we identified CD14 as a cell surface antigen of ML-club cells and showed that purified CD14 + club cells engrafted into injured mouse lungs had better engraftment rate and expansion than other major lung stem cells, reflecting the observations in organoid culture systems. The scMORN method could be adapted to different stem cell tissues to discover useful stem-cell subpopulations.

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          Most cited references45

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          Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets.

          Cells, the basic units of biological structure and function, vary broadly in type and state. Single-cell genomics can characterize cell identity and function, but limitations of ease and scale have prevented its broad application. Here we describe Drop-seq, a strategy for quickly profiling thousands of individual cells by separating them into nanoliter-sized aqueous droplets, associating a different barcode with each cell's RNAs, and sequencing them all together. Drop-seq analyzes mRNA transcripts from thousands of individual cells simultaneously while remembering transcripts' cell of origin. We analyzed transcriptomes from 44,808 mouse retinal cells and identified 39 transcriptionally distinct cell populations, creating a molecular atlas of gene expression for known retinal cell classes and novel candidate cell subtypes. Drop-seq will accelerate biological discovery by enabling routine transcriptional profiling at single-cell resolution. VIDEO ABSTRACT.
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            Single Lgr5 stem cells build crypt-villus structures in vitro without a mesenchymal niche.

            The intestinal epithelium is the most rapidly self-renewing tissue in adult mammals. We have recently demonstrated the presence of about six cycling Lgr5(+) stem cells at the bottoms of small-intestinal crypts. Here we describe the establishment of long-term culture conditions under which single crypts undergo multiple crypt fission events, while simultanously generating villus-like epithelial domains in which all differentiated cell types are present. Single sorted Lgr5(+) stem cells can also initiate these cryptvillus organoids. Tracing experiments indicate that the Lgr5(+) stem-cell hierarchy is maintained in organoids. We conclude that intestinal cryptvillus units are self-organizing structures, which can be built from a single stem cell in the absence of a non-epithelial cellular niche.
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              Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells.

              It has long been the dream of biologists to map gene expression at the single-cell level. With such data one might track heterogeneous cell sub-populations, and infer regulatory relationships between genes and pathways. Recently, RNA sequencing has achieved single-cell resolution. What is limiting is an effective way to routinely isolate and process large numbers of individual cells for quantitative in-depth sequencing. We have developed a high-throughput droplet-microfluidic approach for barcoding the RNA from thousands of individual cells for subsequent analysis by next-generation sequencing. The method shows a surprisingly low noise profile and is readily adaptable to other sequencing-based assays. We analyzed mouse embryonic stem cells, revealing in detail the population structure and the heterogeneous onset of differentiation after leukemia inhibitory factor (LIF) withdrawal. The reproducibility of these high-throughput single-cell data allowed us to deconstruct cell populations and infer gene expression relationships. VIDEO ABSTRACT.
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                Author and article information

                Contributors
                Journal
                Stem Cells
                Stem Cells
                stmcls
                Stem Cells
                Oxford University Press (US )
                1066-5099
                1549-4918
                August 2023
                20 July 2023
                20 July 2023
                : 41
                : 8
                : 809-820
                Affiliations
                Laboratory for Lung Development and Regeneration, RIKEN Center for Biosystems Dynamics Research , Kobe, Japan
                Department of Drug Modality Development , Osaka Research Center for Drug Discovery, Otsuka Pharmaceutical Co., Ltd., Minoh, Japan
                Laboratory for Lung Development and Regeneration, RIKEN Center for Biosystems Dynamics Research , Kobe, Japan
                Department of Regenerative and Infectious Pathology, Hamamatsu University School of Medicine , Higashi-ku, Hamamatsu, Japan
                Laboratory for Lung Development and Regeneration, RIKEN Center for Biosystems Dynamics Research , Kobe, Japan
                Laboratory for Prediction of Cell Systems Dynamics, RIKEN Center for Biosystems Dynamics Research , Suita, Japan
                Laboratory for Lung Development and Regeneration, RIKEN Center for Biosystems Dynamics Research , Kobe, Japan
                Laboratory for Lung Development and Regeneration, RIKEN Center for Biosystems Dynamics Research , Kobe, Japan
                Laboratory for Lung Development and Regeneration, RIKEN Center for Biosystems Dynamics Research , Kobe, Japan
                Laboratory for Prediction of Cell Systems Dynamics, RIKEN Center for Biosystems Dynamics Research , Suita, Japan
                Laboratory for Lung Development and Regeneration, RIKEN Center for Biosystems Dynamics Research , Kobe, Japan
                Author notes
                Corresponding author: Mitsuru Morimoto, Laboratory for Lung Development and Regeneration, RIKEN Center for Biosystems Dynamics Research, Kobe 650-0047, Japan. Tel: +81 78 306 3198; Email: mitsuru.morimoto@ 123456riken.jp
                Author information
                https://orcid.org/0000-0001-9132-4155
                Article
                sxad044
                10.1093/stmcls/sxad044
                10427966
                37468433
                5abc67e2-5fe4-4b8b-b8f0-476f2670f1d7
                © The Author(s) 2023. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License ( https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com.

                History
                : 14 September 2022
                : 15 May 2023
                : 20 July 2023
                Page count
                Pages: 12
                Funding
                Funded by: RIKEN BDR-Otsuka Pharmaceutical Collaboration Center;
                Categories
                Stem Cell Technology: Epigenetics, Genomics, Proteomics, and Metabonomics
                AcademicSubjects/SCI00960

                Molecular medicine
                lung,adult stem cells,alveolar epithelial cells,bronchiolar epithelial cells,organoids,single cell analysis,morphometrics

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