Recapitulating the human segmentation clock with pluripotent stem cells

Last updated: 04-13-2020

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Recapitulating the human segmentation clock with pluripotent stem cells

Recapitulating the human segmentation clock with pluripotent stem cells
Nature volume 580, pages124–129(2020) Cite this article
5563 Accesses
Musculoskeletal development
Abstract
Pluripotent stem cells are increasingly used to model different aspects of embryogenesis and organ formation 1 . Despite recent advances in in vitro induction of major mesodermal lineages and cell types 2 , 3 , experimental model systems that can recapitulate more complex features of human mesoderm development and patterning are largely missing. Here we used induced pluripotent stem cells for the stepwise in vitro induction of presomitic mesoderm and its derivatives to model distinct aspects of human somitogenesis. We focused initially on modelling the human segmentation clock, a major biological concept believed to underlie the rhythmic and controlled emergence of somites, which give rise to the segmental pattern of the vertebrate axial skeleton. We observed oscillatory expression of core segmentation clock genes, including HES7 and DKK1, determined the period of the human segmentation clock to be around five hours, and demonstrated the presence of dynamic travelling-wave-like gene expression in in vitro-induced human presomitic mesoderm. Furthermore, we identified and compared oscillatory genes in human and mouse presomitic mesoderm derived from pluripotent stem cells, which revealed species-specific and shared molecular components and pathways associated with the putative mouse and human segmentation clocks. Using CRISPR–Cas9-based genome editing technology, we then targeted genes for which mutations in patients with segmentation defects of the vertebrae, such as spondylocostal dysostosis, have been reported (HES7, LFNG, DLL3 and MESP2). Subsequent analysis of patient-like and patient-derived induced pluripotent stem cells revealed gene-specific alterations in oscillation, synchronization or differentiation properties. Our findings provide insights into the human segmentation clock as well as diseases associated with human axial skeletogenesis.
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Fig. 1: Molecular and functional analysis of human PSC-derived PSM.
Fig. 2: Identification of phase and antiphase oscillating genes of in vitro human and mouse segmentation clocks.
Fig. 3: Functional evaluation of targeted disruption of selected segmentation clock genes in human in vitro PSM.
Fig. 4: In vitro recapitulation and molecular analysis of disease-phenotypes using patient iPS cells and isogenic controls.
Data availability
All RNA sequencing data used for this study have been deposited in the NCBI Gene Expression Omnibus  (GEO) under accession number GSE116935 . SNP array data in the current publication have been deposited in and are available upon application from the dbGaP database under accession number phs001975.v1.p1 and their use is limited to health, medical and biomedical purposes. Source Data for Figs. 1 – 4 and Extended Data Figs. 1 , 2 , 5– 12 are available in the online version of the paper.
Code availability
Computational codes and scripts used in this study are available at GitHub ( https://github.com/mebisuya/SegmentationClock ) and upon request from the corresponding authors.
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Acknowledgements
The authors thank B. McIntyre and P. O’Neill for critical reading of the manuscript; K. Mitsunaga for help with FACS analysis; Y. Ashida for help with development of human spheroid PSM-induction protocol; H. Hayashi for help with development of mouse PSM protocol; J. Asahira for help with RNA-seq experiments; A. Yamashita for help with 3D chondrogenic induction experiments; M. Shibata and T. Nakajima for help with development of one-step PSM-induction protocol; M. Ohno and S. Nishimura for help with iPS cell quality control and validation; members of the Kageyama laboratory, K. Yoshioka-Kobayashi and A. Isomura for help with Hilbert transformation and M. Matsumiya for help with removing spike noise from images; the CiRA Genome Evaluation Group, in particular H. Dohi, F. Kitaoka, M. Nomura, T. Takahashi, M. Umekage and N. Takasu for performing SNP array analysis. This work was supported by the CiRA Fellowship Program of Challenge to C.A.; Naito Foundation Research Grant to C.A.; Grant-in-Aid for Challenging Exploratory Research (KAKENHI Number 16K15664) to C.A.; Grant-in-Aid for Scientific Research on Innovative Areas (KAKENHI Number 17H05777) to M.M.; Takeda Science Foundation Grant to M.E.; Japan Agency for Medical Research and Development (AMED) Grants Number 12103610 and 17935423 to M.K.S. for iPS cell generation and qualification, grant number JP19bm0804001 to K.W. for iPS cell gene editing and grant numbers JP18ek0109212 and 18ek0109280 to S.I. for genomic and exome studies of spondylocostal dysostosis, respectively; the Core Center for iPS Cell Research (AMED) to T.Y., K.W. and J.T. and the Acceleration Program for Intractable Disease Research Using Disease Specific iPS Cells (AMED) to K.W., J.T. and M.K.S.; the Kyoto University Hakubi Project to K.W.; the Cooperative Research Program (Joint Usage/Research Center Program) of the Institute for Frontier Life and Medical Sciences, Kyoto University to J.T., L.G and S.I.. ASHBi is supported by the World Premier International Research Center Initiative (WPI), MEXT, Japan.
Author information
These authors contributed equally: Mitsuhiro Matsuda, Yoshihiro Yamanaka
Affiliations
Laboratory for Reconstitutive Developmental Biology, RIKEN Center for Biosystems Dynamics Research (RIKEN BDR), Kobe, Japan
Mitsuhiro Matsuda
European Molecular Biology Laboratory (EMBL) Barcelona, Barcelona, Spain
Mitsuhiro Matsuda
 & Miki Ebisuya
Department of Cell Growth and Differentiation, Center for iPS Cell Research and Application (CiRA), Kyoto University, Kyoto, Japan
Yoshihiro Yamanaka
Institute for the Advanced Study of Human Biology (ASHBi), Kyoto University, Kyoto, Japan
Yoshihiro Yamanaka
, Takuya Yamamoto
 & Cantas Alev
Department of Regeneration Science and Engineering, Institute for Frontier Life and Medical Sciences, Kyoto University, Kyoto, Japan
Maya Uemura
, Hiroyuki Yoshitomi
 & Junya Toguchida
Department of Clinical Application, Center for iPS Cell Research and Application (CiRA), Kyoto University, Kyoto, Japan
Mitsujiro Osawa
, Megumu K. Saito
 & Ayako Nagahashi
Laboratory for Bone and Joint Diseases, RIKEN Center for Integrative Medical Sciences (RIKEN IMS), Tokyo, Japan
Long Guo
 & Shiro Ikegawa
Department of Life Science Frontiers, Center for iPS Cell Research and Application (CiRA), Kyoto University, Kyoto, Japan
Satoko Sakurai
, Takuya Yamamoto
 & Knut Woltjen
Department of Fundamental Cell Technology, Center for iPS Cell Research and Application (CiRA), Kyoto University, Kyoto, Japan
Shunsuke Kihara
Department of Orthopedics and Spine Surgery, Meijo Hospital, Nagoya, Japan
Noriaki Kawakami
AMED-CREST, AMED 1-7-1 Otemachi, Chiyodaku, Tokyo, Japan
Takuya Yamamoto
Medical-Risk Avoidance Based on iPS Cells Team, RIKEN Center for Advanced Intelligence Project (AIP), Kyoto, Japan
Takuya Yamamoto
Google Scholar
Contributions
C.A. conceived, designed and supervised the study; M.E. and M.M. conceived and developed mouse PSM-induction and human spheroid PSM-induction protocols and performed 2D-oscillation and 3D-synchronization assays with the help of C.A.; Y.Y., M.U. and C.A. developed stepwise PSM induction and other subsequent differentiation protocols and performed the majority of remaining in vitro and in vivo experiments; S.K. supported microscopy and calcium imaging; M. Nishio helped with xenotransplantation experiments; M.O., M.K.S. and A.N. established patient iPS cell lines used in this study and performed quality control of iPS cells; M.O. helped with FACS data analysis; L.G. and S.I. performed exome sequencing and database analysis; T.Y. analysed RNA-seq and RT–qPCR data with the help of S.S.; K.W. designed gene-knockout and gene-editing strategies; T.L.M. established HES7 c.73C>T (R25W) mutant iPS cells; T.M. performed gene editing of patient iPS cells and Southern blotting; M. Nakamura performed sequence genotyping of patient and gene-edited iPS cells; Y.Y., M.U. and C.A. generated knockout lines with the help of M. Nakamura and K.W. and performed molecular and functional assays using knockout lines, patient-like and patient-derived iPS cells and gene-corrected isogenic controls; M.I. developed one-step PSM induction protocol; M.K.S. and H.Y. shared reagents and protocols; J.T. provided administrative support and, with N.K., helped with establishment of patient lines; C.A. analysed and interpreted the data and wrote the manuscript with the support of M.E. and K.W. All authors discussed and commented on the manuscript and agreed on the presented results.
Corresponding authors
The authors declare no competing interests.
Additional information
Peer review information Nature thanks Helen M. Blau, Duncan Sparrow and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data figures and tables
Extended Data Fig. 1 Characterization of stepwise-induced human PSM.
a, Heat map of gene expression levels in stepwise-induced human PSM and its derivatives (using iPS cell line 1231A3). FPKM values of each gene were normalized to the mean of all samples. The gene order is the same as in Fig. 1b . b, PCA plot of transcript expression levels in human PSM and derivatives of three independent experiments (1231A3), n = 3. Proposed RNA-seq-based developmental trajectory is shown in pink. c, RT–qPCR-based validation of RNA-seq results; data of four independent experiments with three technical replicates each using 201B7 are shown. Data are mean ± s.d., n = 4. Similar results were obtained for 1231A3 (data not shown). Open circles in some conditions indicate that there are less than four experiments because no Ct values for these samples were obtained after 45 cycles of PCR to calculate expression values. d, Representative flow cytometric evaluation of DLL1 and TBX6 (left) and DLL1 and brachyury (BRA) (right) expression at PSM stage (1231A3), n = 3. e, Representative expression of DLL1 at transcript level during in vitro differentiation (201B7). Data are mean ± s.d., n = 4. f, Representative expression of DLL1 at protein level, n = 3. Correlation of FACS data with RT–qPCR results (201B7) shown in e. Source data
Extended Data Fig. 2 Characterization of human segmentation clock period in in vitro PSM.
a, HES7 reporter activity in a 2D culture (the oscillation assay condition) and 3D spreading spheroid (the synchronization assay condition). Raw, detrended (± 100 min window) and phase signals are shown. For spheroids, the signal was averaged over all area or ROIs indicated by the red line. 2D culture data are same as Fig. 1g and part of 3D-spheroid culture data are same as Fig. 1h . Data of three independent experiments are shown. Schematic depiction of reporter construct is shown on top. b, Human segmentation clock period quantification based on detrended and instantaneous phase signals. The period was calculated as the average peak-to-peak interval using the 1st to 5th peaks. The measure of centre is mean, n = 3. c, Instantaneous phase-based kymograph of travelling-wave-like HES7 reporter activity in spheroid spreading assay shown in Fig. 1h . Representative data of three independent experiments are shown. Source data
Extended Data Fig. 3 Characterization of induced human PSM-derivatives, somitic mesoderm, sclerotome and dermomyotome.
a, Representative immunofluorescence staining of PSM markers TBX6 and brachyury (BRA) and somitic mesoderm marker TCF15 at PSM stage, n = 3; entire wells (left) and magnified views of selected areas. b, Representative immunofluorescence staining of PSM markers TBX6 and BRA and somitic mesoderm marker TCF15 at stage, n = 3; entire wells (left) and magnified views of selected areas. Bottom, staining of segmentation marker MESP2 (alone or co-staining with TBX6). Scale bar, 100 μm. c, Representative immunofluorescence of dermomyotome markers (PAX7 and PRRX1) and sclerotome marker (FOXC2) at dermomyotome and sclerotome stages (201B7), n = 3; entire wells (left) and magnified views of selected areas (right). Staining of PAX7 (epithelial colonies) at dermomyotome and FOXC2 (mesenchymal colonies) at sclerotome stage. PRRX1 staining surrounding PAX7+ areas is specific to dermomyotome stage. Scale bar, 100 μm.
Extended Data Fig. 4 Functional evaluation of human iPS cell-derived sclerotome.
a, Assessment of in vivo bone- and cartilage-forming ability of human induced sclerotome. Subcutaneous transplantation of PSC-derived sclerotome stepwise-induced from healthy control or wild-type (1231A3) and luciferase-reporter iPS cell lines (625-D4 and 625-A4). Evaluation of transplanted cells using IVIS at two months after transplantation; injection sides are marked with dashed or coloured circles. Cartilage and bone-forming areas of wild-type iPS cell line (1231A3) marked by white arrows. b, Whole-mount images of wild-type sclerotome-derived in vivo cartilage and bone tissues isolated from transplanted mice 1 and 3. Explant isolated from mouse 2 is shown in d. Scale bar, 4 mm. c, Representative staining of in vitro human sclerotome-derived cartilage (from 3D chondrogenic induction) sections. Observed safranin O and type II collagen (COL2) signals are indicative of in vitro cartilage formation, n = 3. d, Representative whole-mount (top left) and histological staining of section (bottom left) of human induced sclerotome-derived in vivo cartilage and bone. Scale bar, 100 μm. Representative pentachrome staining of marked area reminiscent of in vivo human endochondral bone formation; n = 3. I, proliferative human cartilage; II, hypertrophic cartilage; III, ossifying cartilage and forming human bone. Scale bar, 100 μm. e, Representative sections and staining of area shown in d. Safranin O and COL2 staining in human in vivo sclerotome-derived cartilage areas; von Kossa and COL1 staining in ossifying cartilage and forming bone areas. Majority of cells contributing to cartilage or bone formation are HNA-positive and of human origin (right bottom); n = 3. Scale bar, 100 μm.
Extended Data Fig. 5 Functional evaluation of human iPS cell-derived dermomyotome.
a, Evaluation of in vitro muscle induction from human induced dermomyotome. Myosin and sarcomeric α-actinin (SAA) staining of in vitro dermomyotome-derived skeletal muscle; representative images of entire well (left) and magnified areas (right); n = 3. Scale bar, 100 μm. b, Comparison of skeletal muscle induction of human iPS cell, and iPS cell-derived sclerotome and dermomyotome. Representative myosin heavy chain (MYH), myosin and sarcomeric α-actinin staining only apparent in dermomyotome-based skeletal muscle differentiation. Right, magnified areas; n = 3. c, Quantification of contracting colonies and GFP-positive foci of iPS cell-, sclerotome- and dermomyotome-derived human skeletal muscle. Calcium-reporter iPS cell line (Gen1C) was used in all cases. Measurements of total 18 view fields in 6 independent experiments. In box-and-whisker plots, the middle line represents median value, box edges represent 25th and 75th quartiles and error bars show extreme values. d, Representative quantification of calcium GFP-reporter activity in iPS cell, sclerotome and dermomyotome as readout of spontaneous contraction-mediated GFP signal in induced human skeletal muscle cells; n = 3. Source data
Extended Data Fig. 6 RNA-seq analysis of human iPS cell-derived oscillating PSM.
a, Sampling of human oscillating PSM samples for RNA-seq. HES7 reporter activity was continuously monitored with one sample, and the other samples were frozen at each time point indicated in the graph. b, Three-dimensional synchronization (spheroid-spreading) assay following inhibition of FGF (PD173074, 100 nM), Notch (DAPT, 10 mM), and Wnt (XAV939, 10 mM) signalling pathways. The HES7 reporter signal was first averaged over all area, the background was subtracted and the signal was normalized to time 0. The background was defined as the average signal at time 0 over the 15 × 15-pixel area of the top left corner of the image. Representative graph of three independent experiments is shown. See also Supplementary Video  3 . c, Average HES7 reporter intensity during 36–41 h (2,160–2,440 min) of inhibitor treatment. Data are mean ± s.d., n = 3; two-sided Dunnett’s test. *P 


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