Blog
About

  • Record: found
  • Abstract: found
  • Article: found
Is Open Access

Long-Term In Vitro Expansion of Epithelial Stem Cells Enabled by Pharmacological Inhibition of PAK1-ROCK-Myosin II and TGF-β Signaling

Read this article at

Bookmark
      There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

      SUMMARY

      Despite substantial self-renewal capability in vivo, epithelial stem and progenitor cells located in various tissues expand for a few passages in vitro in feeder-free condition before they succumb to growth arrest. Here, we describe the EpiX method, which utilizes small molecules that inhibit PAK1-ROCK-Myosin II and TGF-β signaling to achieve over one trillion-fold expansion of human epithelial stem and progenitor cells from skin, airway, mammary, and prostate glands in the absence of feeder cells. Transcriptomic and epigenomic studies show that this condition helps epithelial cells to overcome stresses for continuous proliferation. EpiX-expanded basal epithelial cells differentiate into mature epithelial cells consistent with their tissue origins. Whole-genome sequencing reveals that the cells retain remarkable genome integrity after extensive in vitro expansion without acquiring tumorigenicity. EpiX technology provides a solution to exploit the potential of tissue-resident epithelial stem and progenitor cells for regenerative medicine.

      Graphical Abstract

      In Brief

      Zhang et al. screen a small-molecule collection and find that pharmacologic inhibition of TGF-β and PAK1-ROCK-Myosin II, in low calcium conditions, supports extended expansion of epithelial stem cells in 2D format. This approach enhances the potential of tissue-resident epithelial stem cells for cell therapy.

      Related collections

      Most cited references 74

      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

      In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
        Bookmark
        • Record: found
        • Abstract: found
        • Article: not found

        An Integrated Encyclopedia of DNA Elements in the Human Genome

        Summary The human genome encodes the blueprint of life, but the function of the vast majority of its nearly three billion bases is unknown. The Encyclopedia of DNA Elements (ENCODE) project has systematically mapped regions of transcription, transcription factor association, chromatin structure, and histone modification. These data enabled us to assign biochemical functions for 80% of the genome, in particular outside of the well-studied protein-coding regions. Many discovered candidate regulatory elements are physically associated with one another and with expressed genes, providing new insights into the mechanisms of gene regulation. The newly identified elements also show a statistical correspondence to sequence variants linked to human disease, and can thereby guide interpretation of this variation. Overall the project provides new insights into the organization and regulation of our genes and genome, and an expansive resource of functional annotations for biomedical research.
          Bookmark
          • Record: found
          • Abstract: found
          • Article: not found

          STAR: ultrafast universal RNA-seq aligner.

          Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
            Bookmark

            Author and article information

            Affiliations
            [1 ]Propagenix, 9605 Medical Center Drive, Suite 325, Rockville, MD 20850, USA
            [2 ]Department of Genetics, Washington University School of Medicine, St. Louis, MO 63108, USA
            [3 ]The Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO 63108, USA
            [4 ]Lead Contact
            [5 ]These authors contributed equally
            Author notes
            [* ]Correspondence: ck.zhang@ 123456propagenix.com (C.Z.), twang@ 123456wustl.edu (T.W.)

            AUTHOR CONTRIBUTIONS

            Conceptualization, C.Z. and T.W.; Methodology, C.Z. and T.W.; Investigation, C.Z., H.J.L., A.S., R.W., and T.J.M.; Writing – Original Draft, C.Z., H.J.L., S.S.C., B.A.P., and T.W.; Writing – Revision, C.Z. and T.W.; Supervision, C.Z., S.S.C., B.A.P., and T.W.

            Journal
            101573691
            39703
            Cell Rep
            Cell Rep
            Cell reports
            2211-1247
            27 October 2018
            16 October 2018
            07 December 2018
            : 25
            : 3
            : 598-610.e5
            30332641
            6284236
            10.1016/j.celrep.2018.09.072
            NIHMS1510941

            This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/).

            Categories
            Article

            Cell biology

            Comments

            Comment on this article