Controlling human organoid symmetry breaking reveals signaling gradients drive segmentation clock waves

Summary

Axial development of mammals involves coordinated morphogenetic events, including axial elongation, somitogenesis, and neural tube formation. To gain insight into the signals controlling the dynamics of human axial morphogenesis, we generated axially elongating organoids by inducing anteroposterior symmetry breaking of spatially coupled epithelial cysts derived from human pluripotent stem cells. Each organoid was composed of a neural tube flanked by presomitic mesoderm sequentially segmented into somites. Periodic activation of the somite differentiation gene MESP2 coincided in space and time with anteriorly traveling segmentation clock waves in the presomitic mesoderm of the organoids, recapitulating critical aspects of somitogenesis. Timed perturbations demonstrated that FGF and WNT signaling play distinct roles in axial elongation and somitogenesis, and that FGF signaling gradients drive segmentation clock waves. By generating and perturbing organoids that robustly recapitulate the architecture of multiple axial tissues in human embryos, this work offers a means to dissect mechanisms underlying human embryogenesis.

Graphical Abstract

In brief:

A robust human stem cell model of axial morphogenesis shows that FGF signaling governs both the dynamics of segmentation clock waves and the somite determination front.

Introduction

The progenitors in the tailbud of the axially elongating mammalian embryo give rise to the posterior neural tube and the flanking presomitic mesoderm (PSM)^1,2. The PSM is further patterned and segmented into somites (Fig 1A), which in turn give rise to the axial skeleton, skeletal muscles, and dorsal dermis³, while the posterior neural tube gives rise to the spinal cord⁴. Periodic and sequential segmentation of PSM into somites is controlled by the segmentation clock, which is a complex network of oscillating genes under the control of NOTCH, FGF, and WNT pathways⁵. The cyclic expression of these genes travels anteriorly through the PSM as a gene expression wave^6–8. When each such segmentation clock wave reaches the anterior end of the PSM, it initiates the segmentation program of the next presumptive somite pair. Thus, the boundary between the somites and the undifferentiated PSM, called the somite determination front, moves posteriorly with every wave. During development, the embryo must coordinate the dynamics of multiple processes, including axial elongation, PSM generation, anterior movement of the segmentation clock waves in the PSM, posterior movement of the somite determination front, and somite segmentation. FGF and WNT pathways are required for axial elongation^9–11 and the differentiation of axial progenitors into presomitic mesoderm¹² in mouse, chick, and zebrafish. In addition, the position of the somite determination front along the anteroposterior axis is thought to be defined by FGF and WNT signaling gradients in different vertebrates^9,13–16. However, the mechanisms underlying the anterior movement of segmentation clock waves and the interaction of these waves with the signaling gradients remain unknown¹⁷.

Fig.1. Elongating axial organoids generates neural tube with a single lumen flanked anteriorly by segmented somites and posteriorly by presomitic mesoderm.

(A) Left: Micrograph of Carnegie Stage 10 human embryo, Kyoto Collection. Right: Target pattern with expression profiles of MESP2,, TBXT and SOX2 colored and overlayed on the posterior part of the human embryo micrograph. (B) Randomly positioned organoids on a coverslip, each consisting of a single epithelial layer of cells enclosing a single lumen, treated with BMP inhibitor LDN193189 (0.5μM), TGFβ inhibitor A83–10 (0.5μM) and WNT agonist CHIR99021 (left to right: 2.5μM, 4μM, 6μM) for 48 hours stained for TBXT and SOX2. Scale bar, 1 mm. (C) Organoids micropatterned in groups of four on the vertices of a square after 48 hours of differentiation, stained for TBXT (left) and SOX2 (middle), color combined (right). Scale bars, 1 mm. (D) Histogram showing the distribution of organoid polarization metric on random arrays for each CHIR concentration and on the vertices of squares at 4μM CHIR concentration. (E) Magnified image of one set of four organoids on the vertices of a square at 48 hours of differentiation stained for TBXT and SOX2. Scale bar, 200μm. (F) Organoids micropatterned in groups of four on the vertices of a square after 48 hours of differentiation with live HES7 reporter signal (green) shown for a full array (top); magnified and overlayed on the phase image for one set of four organoids (bottom). One hundred percent of the organoids on coverslips show polarized expression HES7. Scale bars: 1mm top, 200μm bottom. (G) Confocal sections of representative organoids with MESP2∷mCherry reporter on consecutive days of differentiation (72 h, 96 h, 120 h, 144 h) stained for TBXT, SOX2. TBXT and SOX2 co-expressing NMPs reside at the posterior tip. MESP2 progression starts anteriorly and moves towards the tip during 144 hours of differentiation. Scale bars, 200μm. (H) Phase contrast images overlayed with MESP2∷mCherry signal in live organoids randomly selected from 144 organoids grown on the same coverslip and transferred to a 96-well low adhesion plate at 120 h of differentiation. All organoids show elongated morphology and lateral MESP2∷mCherry expression. Scale bar: 1mm. (I) Top: Quantification of elongation. Box plot of length of the organoids on 72h, 96h, and 120h of differentiation. Dots are individual data points. Center line, median; box, interquartile range; whiskers, range not including outliers; empty circles: outliers. n= 95 independent biological replicates. Bottom: Quantification of MESP2 reporter expression along the anteroposterior axis of the organoids on 72h, 96h, and 120h of differentiation. Solid lines: means; shaded area: std. AU, arbitrary units. n=95 independent biological replicates. (J) Confocal section of a representative organoid with MESP2:mCherry reporter stained for tight junction marker ZO-1 and SOX1 at 120h of differentiation. Scale bars: 100μm. (K) Epifluorescence image of a representative organoid with MESP2:mCherry reporter stained for paraxial mesoderm marker TBX6 and neural marker SOX1 at 120h of differentiation. Color combined fluorescence images overlayed on phase contrast image (right-most image). Scale bars: 100μm. (L) Confocal section of a representative organoid showing alternating expression of MESP2 reporter on 120 h of differentiation, stained for DAPI. Scale bar, 200μm.

The challenges in measuring and perturbing the dynamics of mouse embryos in utero and the ethical challenge in studying human development necessitate using in vitro systems. Recently, oscillating gene expression patterns and the generation of somitic mesoderm have been reported in monolayer cultures of human pluripotent stem cell-derived PSM cells, which is the first evidence for the existence of a segmentation clock in humans^18–20. In exciting recent work, mouse and human stem cell-derived organoids have been directed to extend axially and generate neural progenitors and somites^21–23. However, the morphological variability from organoid to organoid and defects in the architecture of the underlying tissues in these in vitro systems significantly limit the use of chemical and genetic perturbations to gain mechanistic insight²⁴. The ability to generate reproducible and robust organoids that recapitulate human axial development is essential for progress. Furthermore, such organoids will allow dynamic measurements and temporally controlled perturbations in a manner that is impossible in vivo.

Here, we aimed to characterize the dynamics of human axial patterning and morphogenesis to understand how segmentation clock waves interact with signaling gradients. Following the methods developed in a companion manuscript²⁵, we employed a combination of machine learning and bioengineering tools to tune the coupling of human pluripotent stem cell organoids by controlling their spatial arrangement. This enabled us to generate hundreds of in vitro organoids simultaneously, each robustly and reproducibly recapitulates the architecture of axial tissues in human embryos. Using single-cell sequencing and computational analysis, we validated the organoids by determining the cell type composition and the spatial profiles of key transcription factors and signaling molecules along the anteroposterior axis. We demonstrated that the organoids recapitulate the dynamics of axial elongation, anteriorly moving segmentation clock waves, posteriorly moving somite determination front, and somite segmentation. By perturbing the organoids, we showed that FGF signaling gradients drive the anterior propagation of segmentation clock waves while simultaneously controlling the movement of the somite determination front, somite segmentation, and, together with WNT, axial elongation. We finally discuss the implications of these results in the context of the existing models for axial patterning of the somites.

Results

Spatially coupled organoids achieve robust A-P symmetry breaking

To understand human axial development, we aimed to generate hundreds of organoids, each with an axially extending tailbud that generates a single lumen neural tube flanked posteriorly by PSM and anteriorly by somites as seen in vivo (Fig. 1A). To achieve this desired outcome, we built upon a bioengineering and machine learning framework developed in a companion manuscript, to reproducibly break anterior-posterior (A-P) symmetry²⁵. We first recapitulated the human epiblast²⁶ by micropatterning human pluripotent stem cells at random locations on a glass coverslip and folding them into 150 μm diameter cysts composed of a single epithelial layer of pluripotent stem cells enclosing a lumen²⁵. To induce differentiation, we exposed the cysts to medium containing WNT agonist CHIR99021 (at concentrations ranging from 2.5μM to 6μM) while inhibiting BMP (LDN193189, 0.5μM) and TGF-β signaling (A83–01, 0.5μM). After 48 hours, we stained the differentiated organoids for SOX2 and TBXT (Fig. 1B, Fig. S1A). These markers were chosen to label the SOX2+TBXT+ neuromesodermal (NMP) progenitors in the tailbud, SOX2− TBXT+ paraxial mesoderm flanking the neural tube posteriorly, and the SOX2+TBXT- cells of the neural tube. In the desired organoid morphology, we expected TBXT to be posteriorly expressed relative to SOX2. We thus scored our organoids using a polarization metric, ${\mu }_{\text{measured}}^{\frac{\mathit{\text{TBXT}}}{\mathit{\text{SOX}}2}}$, defined as the distance between the centroid of TBXT+ cells and that of SOX2+ cells in each organoid (Fig. 1A). The organoids on the random pattern showed a large variability in ${\mu }_{\text{measured}}^{\frac{\mathit{\text{TBXT}}}{\mathit{\text{SOX}}2}}$ (Fig. 1B and D). Using the approach in Anand et al., we optimized the spatial arrangement of the differentiating organoids on a coverslip and the CHIR concentration such that each organoid broke A-P symmetry to acquire a large ${\mu }_{\text{measured}}^{\frac{\mathit{\text{TBXT}}}{\mathit{\text{SOX}}2}}$. This arrangement consisted of 150μm diameter organoids in groups of four at the vertices of 200 by 200 μm squares (Fig. 1C, Fig. S1A). After exposure to 4μM CHIR for 48 hours, every organoid broke A-P symmetry and was polarized with low SOX2/ high TBXT posteriorly and high SOX2/ low TBXT anteriorly (Fig. 1C–E, Fig. S1A). To visualize this polarization in live organoids, we used a dual fluorescence reporter HES7:Achilles/MESP2:mCherry iPSC line¹⁸, allowing us to monitor the polarization of the presomitic mesodermal marker HES7 (Fig. 1F).

Polarized organoids with posteriorly localized NMPs generate a single-lumen neural tube flanked by segmented somites

After the initial A-P symmetry breaking at 48 hours, randomly selected 96 organoids of the 144 on the same coverslip were removed and cultured individually in low adhesion 96 well plates in basal media (E6) supplemented with Matrigel, without any signaling molecules or inhibitors. From 72 to 120 hours after the start of differentiation, all the organoids that were successfully transferred to the 96 well plate underwent axial elongation (Fig. 1H and I, Fig. S1C). They also contained a TBXT+SOX2+ NMP population at the posterior tip that was maintained throughout 120 hours of differentiation (Fig. 1G, Fig. S1D). Every organoid showed lateral expression of the somitogenesis marker MESP2 based on mCherry expression (Fig. 1H) and displayed anterior to posterior progression of the MESP2+ somite fate (Fig 1H–I, Fig. S1C, n=95).

We next determined the expression patterns of key proteins in these organoids at 120h through immunostaining. Every organoid had an anteriorly positioned SOX1+ and SOX2+ neural tube with a single lumen and the proper apicobasal polarity as shown by ZO-1 and N-cadherin stains marking the apical tight junctions between epithelial cells (Fig 1J, Fig. S1G and H). In each organoid, the neural tube was flanked posteriorly by TBX6+ paraxial mesoderm and anteriorly by the MESP2+ somite cells (Fig. 1K, Fig. S1E). ZO-1 and N-cadherin expression was localized in multiple foci in the MESP2+ somite region, showing the segmented architecture of somites flanking the anterior neural tube (Fig 1J, Fig S1G and H). Similar to the A-P organization of the developing embryo²⁷, the TBX6-expressing domain formed a clear boundary corresponding to the somite determination front, posterior to the MESP2+ cells (Fig. 1K, Fig. S1E, and F). By 120 hours of differentiation, the MESP2 expression pattern had resolved into an alternating pattern in each segment as seen in vivo^27–29, indicating that the somites displayed A-P compartmentalization (Fig 1L). These results together demonstrate that our approach robustly achieved the differentiation of pluripotent stem cells into organoids with correctly positioned tailbud, neural tube, and somite structures, capturing key aspects of in vivo axial development.

Clustering and diffusion map analysis of axial organoid transcriptome reveals cell types and A-P organization of neural tube and paraxial mesoderm

To explore the cell type composition of organoids, we performed single-cell RNA sequencing of 11009 cells obtained from 10 organoids at 120 h (Fig. S2A). Clustering and identifying cell types from this data requires measuring the distance between cells in gene expression space. The Euclidean distance in the space of all high-variance genes leads to incorrect clustering and classification³⁰. To overcome this challenge, we previously developed and validated an unsupervised statistical method, sparse multimodal decomposition (SMD), to identify the key subset of genes that can be used to determine cell types³¹. Using SMD, we identified 48 key genes with significant z-scores from the single-cell data (Fig. 2A, Fig. S2B). Through hierarchical clustering in this gene subspace, we identified seven cell types in the organoids (Fig 2, A and B, Fig. S2, B, and C). The first cluster co-expressed TBXT and SOX2, indicating a neuromesodermal progenitor identity¹. The second cluster, consisting of SOX2+TBXT- cells, co-expressed tailbud genes HOXA10, CDX2, and NKX1–2, consistent with a pre-neural tube identity³². A third cluster possessed a neural progenitor identity, expressing neural markers SOX1, PAX6, HES5, and IRX3 along with high levels of SOX2⁴. Three additional clusters were associated with paraxial mesodermal identity. These included a presomitic mesoderm-like cell cluster expressing TBX6, MSGN1, and HES7, an early somite cell cluster expressing MEOX1, TCF15, and RIPPLY1, and a mature somite cell cluster expressing PAX3, TWIST1, and FST³³. Lastly, we identified a small number of notochord cells expressing SHH, NOTO, and high levels of TBXT^34,35.

Fig.2. Anteroposterior organization of cell types and gene expression profiles inferred from single-cell RNA-seq.

(A) Normalized gene expression heatmap of 11009 cells from 120 h organoids, hierarchically clustered in the subspace of 48 genes identified by sparse multimodal decomposition. The inferred identities of the 7 clusters are labeled below. (B) UMAP (uniform manifold approximation and projection) plot generated in the subspace of genes identified by sparse multimodal decomposition. Cells are colored by their cluster identity (see legend for color code, same as in A). Inset shows the UMAP plot colored by inferred anteroposterior positions of cells obtained by diffusion mapping (see Methods). (C and D) Heatmap of top 200 differentially expressed genes (y-axis) in the mesodermal (C) cell clusters (presomitic mesoderm, early somite, and somite) and neural (D) cell clusters (pre-neural tube and neural progenitors) in cells (x axis) ordered according to their inferred anteroposterior positions. Genes are ordered based on the position of their peak expression on the inferred A-P axis. Color bars on the top of heatmaps represent the cluster identity of the individual cells (same color code as in A). (E and F) Normalized posterior-anterior gene expression profiles for marker genes of mesodermal (E, top) and neural cell clusters (E, bottom); FGF pathway ligands and targets (F, top left), WNT pathway ligands and targets (F, bottom left) in neural clusters; FGF pathway ligands (F, top middle) and targets (F, top right), WNT pathway ligands (F, bottom middle) and targets (F, bottom right) in mesodermal cell clusters. Bars on the top of each plot represent cells at that position along the inferred P-A axis, colored by their cluster identity (same color code as in A). (G) Confocal images of organoids stained for WNT3A, FGF8, FGF4, CYP26A1, ALDH1A2 using HCR (columns from left to right). WNT3A, FGF8, FGF4, and CYP26A1 are localized posteriorly and have a graded expression on the anteroposterior axis. ALDH1A2 is localized anteriorly, expressed only in somite cells. Scale bar, 200μm.

To map the spatial distribution of neural and mesodermal lineages present in organoids from scRNA-seq data, we constructed a diffusion map³⁶ in the subspace of genes identified by SMD (Fig 2B). We previously showed that such a map could recapitulate the spatial ordering of cells along the A-P axis, allowing the inference of spatial profiles of gene expression²⁵. We plotted the expression levels of genes arranged in order of the position of their peak expression level along the inferred posterior to anterior axis in both the neural and mesodermal tissues (Fig. 2, C, and D). In the mesodermal cells, genes expressed in the tailbud progenitors (TBXT, CDX1, CDX2, CDX4, LIN28A, HOXA10, HOXC10) peak most posteriorly, followed by the marker genes of presomitic mesoderm (TBX6, DLL3, DLL1, MSGN1), followed by the somite determination front marker MESP2, then early somite markers (MEOX1, RIPPLY1, TCF15), and finally mature somite markers (SIX1, PAX3, ALCAM)³⁷(Fig. 2, C and E, Fig. S2D). Along the neural lineage, cells closest to the neuromesodermal progenitors expressed pre-neural tube markers CDX2, MSX1, and NKX1–2 (Fig. 2D, Fig. S2D). On the other hand, anteriorly positioned cells expressed higher levels of neural progenitor markers SOX1, PAX6, OLIG3, and IRX2, together with higher levels of SOX2⁴(Fig. 2, D and E, Fig. S2D). We verified the inferred anterior-posterior (A-P) expression profiles of the marker genes by MESP2:mCherry reporter expression and immuno-staining against TBXT, TBX6 (Fig. S1, D, and E) and for mesodermal cells and SOX2, SOX1 and PAX6 for neural cells (Fig. S2H, S1D).

Inferring the anteroposterior profiles of WNT, FGF, RA, NOTCH, and BMP signaling pathway components in the mesodermal and neural tissues

We next tested whether our organoids recapitulated the anteroposterior expression gradients of WNT, FGF, RA, and NOTCH signals and their targets as observed in vivo in mouse, chick, and zebrafish embryos^4,38. The expression profile of the detected FGF ligands in neural cells (FGF8, FGF17, Fig. 2F) and mesodermal cells (FGF3, FGF4, FGF8, FGF17, Fig. 2F) were localized most posteriorly in each lineage. FGF receptors were differentially expressed between the mesoderm and neural tissues, with FGFR1 expressed throughout the mesoderm and FGFR2 showing monotonically increasing levels from posterior to anterior in the neural tube (Fig. S2E). In both tissues, FGF target genes SPRY4 and ETV4 were upregulated posteriorly (Fig. 2F), consistent with the role of FGF in maintaining the axial progenitor state in the tailbud of the mouse embryo^15,39.

Like FGF, all detected WNT ligands showed a posterior to anterior graded expression. While both canonical (WNT3A, WNT8A) and noncanonical (WNT5A, WNT5B) WNT ligands were expressed in the mesodermal tissue (Fig. 2F), only noncanonical (WNT5A, WNT5B) WNT ligands showed expression in the neural tissue (Fig. 2F). The WNT ligand expression gradient was opposed by an expression gradient of secreted WNT inhibitors SFRP1 and SFRP2 in both mesoderm and neural lineages (Fig. S2F). WNT targets (CDX2, CDX1, SP5) showed a posteriorly restricted expression pattern in the neural tissue similar to that of WNT ligands (Fig. 2F). In the mesodermal tissue, one class of WNT targets (TBXT, CDX2, CDX4), was highly expressed at the posterior end of the tissue and downregulated anteriorly. The second class of targets (AXIN2, DLL1) and the WNT transcriptional mediator LEF1 showed peak expression at the anterior end of the presomitic mesoderm closest to the somite determination front (Fig. 2F).

Retinoic acid signaling is important in mouse embryos for the fate specification of NMPs, differentiation of presomitic mesoderm, and the patterning of the neural tube¹. We observed that in our organoids, while the retinoic acid receptor gamma (RARG) was expressed throughout the neural and mesodermal tissues, the retinoic acid synthesis gene ALDH1A2 was expressed only in the somites anteriorly (Fig. S2G). Anterior retinoic acid secretion from somites combined with the posterior expression of the retinoic acid degradation enzyme CYP26A1 (Fig. S2G) is consistent with an A-P retinoic acid gradient. Anterior upregulation of transcription factor PAX6 known to be downstream of retinoic acid signaling⁴⁰ suggested that the neural tube was patterned by retinoic acid secreted by the flanking somites. Consistent with this, immunostaining showed upregulation of PAX6 protein in the section of the neural tube in proximity to the somites (Fig. S2H).

Next, we investigated the NOTCH signaling pathway, a key component in regulating periodic somite segmentation and neurogenesis^41,42. In the mesodermal lineage, both NOTCH pathway ligands (DLL1, DLL3), receptor (NOTCH1), and targets (HES6, HES7) were highly expressed in the presomitic mesoderm and downregulated anterior to the somite determination front (Fig. S2I). Although the NOTCH receptor expression levels were very low in the neural tissue, NOTCH ligand DLL1 and NOTCH target gene HES5 were upregulated in the neural progenitors anteriorly, suggesting the initiation of neurogenesis (Fig. S2I).

To validate the computationally inferred anteroposterior expression profiles of genes involved in signaling, we performed in situ hybridization chain reaction (HCR) for WNT3A, FGF8, FGF4, CYP26A1, and ALDH1A2 on organoids upon 120h of differentiation (Fig. 2G). Consistent with the inferred profiles, WNT3A (n = 3), FGF8 (n = 5), FGF4 (n = 3), and CYP26A1 (n = 3) had posterior to anterior graded expression, while ALDH1A2 (n = 3) expression was localized anteriorly at somites. Further, to determine whether the anteroposterior expression gradients of WNT and FGF ligands were reflected in the signaling pathway activity, we immunostained organoids for diphosphorylated ERK (dpERK) and β-catenin (Fig. S2, L, and M). Nuclear segmentation and quantification of dpERK and β-catenin signals showed that the signaling activity for both FGF and WNT pathways was high at the posterior tip and gradually decreased anteriorly (Fig. S2, L, and M). In total, our human organoid model shows anteroposterior expression gradients of WNT, FGF, RA, and NOTCH signals and targets consistent with in vivo observations in mouse, chick, and zebrafish embryos.

The dorsoventral patterning of somites and the neural tube is regulated by opposing gradients of BMPs secreted by surface ectoderm, roof plate, and somites, and SHH secreted by the notochord and floor plate⁴³. While our organoids lack roof plate and floor plate cell types, BMP7 was expressed by neuromesodermal progenitors and the posterior presomitic mesoderm, and BMP4 and BMP3 were expressed by somites (Fig. S2J). The presence of dorsalizing signals was consistent with acquiring a dorsal identity by both neural progenitor cells and somite cells. Neural progenitor cells expressed dorsal neural tube markers MSX1, OLIG3, IRX3 and PAX3,⁴⁴, and somite cells expressed a dermomyotome marker PAX3³³, seen only dorsally in somites in vivo. In contrast, the ventral somite marker PAX1⁴⁵ was not expressed in any cells (Fig. S2J), consistent with the lack of SHH expression by cells. We also observed the expression of a neural crest marker SOX9 and the epithelial-to-mesenchymal transition gene SNAI2 in a subset of neural progenitors (Fig. S2K). Thus, in the absence of SHH, tailbud progenitors generated only dorsal neural and mesodermal cell types, possibly through the dorsalizing effect of BMPs secreted by mesodermal cells.

We compared our single cell RNA sequencing data with a previously published single cell RNA sequencing data obtained from E9.5 mouse embryo tail bud¹⁸. The cell types identified in our axial organoid model were consistent with their in vivo counterparts (see Methods, Fig 3S A–E).

Fig.3. Dynamics of Somitogenesis and NOTCH gene expression waves in the organoids.

(A) Stills from time-lapse imaging of organoids (at 74.5h, 80.75h, 87h, and 93.25h after onset of differentiation) with HES7 (green) and MESP2 (red) expression reporters. All organoids show oscillating HES7 expression and posteriorly propagating MESP2+ somite determination front. Scale bars, 500μm. (B) Stills from time-lapse imaging of the organoid are highlighted with a black box in (A) from 96h to 112.5h. Organoid shows anteriorly propagating HES7 (green) expression waves and posteriorly propagating MESP2 (red) somite determination front. Time interval between consecutive images is 45 minutes. Scale bar, 100μm. (C) Representative kymograph showing the dynamics of HES7 (green) and MESP2 (red) expression along the anteroposterior axis of organoids from 72 h to 122 h of differentiation. Data collected every 15 minutes. (D) HES7 (green) expression at the most anterior tip of the presomitic mesoderm and the length of the MESP2 (red) expressing region of a representative organoid over time. Data collected every 15 minutes. Thicker lines show the moving average with a window size of 3 time points, and shaded areas show moving standard deviation with a window size of 3 time points. Black dots represent each data point. AU, arbitrary units. (E) Plot showing period (left axis, green) and phase (right axis, red) of the oscillations along the anteroposterior axis of presomitic mesoderm of organoids. Lines represent mean and shaded area represent standard deviation over n=14 biologically independent replicates. (F) Left: Representative kymograph showing the dynamics of HES7 (green) and MESP2 (red) expression along the anteroposterior axis of organoids from 72h to 114h of differentiation upon NOTCH inhibition using DAPT. Right: HES7 (green) expression at the most anterior tip of the presomitic mesoderm and the length of the MESP2 (red) expressing region of a representative organoid over time upon NOTCH inhibition. Data collected every 15 minutes for both plots. Thicker lines show the moving average with a window size of 3 time points, and shaded areas show moving standard deviation with a window size of 3 time points. Black dots represent each data point. AU, arbitrary units. Red arrow indicates time of DAPT addition.

Axial organoids show sequential somite segmentation coordinated with traveling segmentation clock waves

Given that the morphology, composition, and signaling profiles of 120-hour-old organoids were consistent with those of mammalian embryos, we next measured the dynamics of somitogenesis. We tested whether the organoids showed anteriorly propagating segmentation clock waves in the PSM and a coordinated posteriorly propagating somite determination front. We performed time-lapse imaging of organoids built with the dual reporter HES7-Achilles/MESP2-mCherry iPSC line. After 72h of differentiation, when the first somite cells appeared at the anterior end, we transferred organoids to individual wells of a glass-bottom 96-well plate for imaging. Each organoid showed oscillating HES7 expression and posteriorly propagating MESP2 expression (Fig. 3, A and B, Fig. S4B, Movie S1, MovieS2). Quantification of Achilles and mCherry signals showed that the MESP2+ region expanded in a step-like fashion. Each step in the MESP2 profile coincided with a peak of HES7 oscillations at the anterior end of the PSM, indicating that the timing of somite differentiation is coordinated with the segmentation clock wave in the axial organoids (Fig. 3, C and D, Fig. S4B). Characterizing the HES7 oscillations along the A-P axis showed transient dynamics with almost synchronous oscillations throughout the PSM when the first somites appear around 72 hours. This is consistent with recent reports in mouse⁴⁶. By 96 hours of differentiation, a global phase gradient was established in 91 % of the organoids (n=54). In these organoids, oscillations at the anterior tip lagged the posterior tip, resulting in anteriorly moving traveling waves (Fig. S4A). By 115 hours of differentiation, all organoids showed anteriorly propagating traveling waves with π/2 radians phase difference between posterior and anterior PSM on average (n=14, Fig. 3E, Fig. S4, A, and C). We also found that the oscillations were faster posteriorly compared to the anterior, with a period of 4.5 hours at the posterior tip and around 5 hours at the anterior PSM. (Fig. 3E). In mouse, chick, and zebrafish embryos, the NOTCH pathway has been implicated in driving intracellular gene expression oscillations and somite segmentation^5,27,41. In line with in vivo studies^47,48, inhibition of NOTCH signaling through DAPT (25μM) treatment resulted in the downregulation of HES7 oscillation amplitude and the impairment of MESP2 progression consistent with MESP2 being a NOTCH target gene (Fig. 3F, Fig. S4D, Movie S2). Thus, our in vitro organoid model recapitulates traveling segmentation clock waves and sequential somite segmentation as observed in vivo.

FGF and WNT pathways have complementary roles in axial elongation, movement of the somite determination front, and somite segmentation.

In our organoids, WNT inhibition using the WNT secretion inhibitor IWP-2 (2μM) added during somitogenesis resulted in truncated organoids with truncated PSM (Fig. 4A and B, Fig. S5A). However, we did not observe an effect of WNT inhibition on the movement of the somite determination front. We continued to see step-like segmentation with segment sizes similar to control organoids (Fig. 4C, Fig. S5A, Movie S2). Consistently, when ectopic WNT activation was uniformly stimulated by CHIR (3μM) addition at 96h of differentiation, organoids were elongated and developed a longer PSM compared to controls (Fig. 4D, Fig. S5, B, and C). These organoids continued to show step like MESP2 progression without a significant change in somitic mesoderm length or defects in segmentation compared to control organoids (Fig. 4, D–F, Fig. S5, B, C, and E). These results show that the WNT pathway directly promotes axial elongation and has little effect on the progression of the determination front or somite segmentation.

Fig.4. FGF drives somite determination front propagation and somite segmentation, while WNT drives axial elongation.

(A and B) Length fold change (A) and presomitic mesoderm length fold change (B) of organoids treated with PD0325901 (1μM, n=5, red), IWP-2 (2μM, n=4), and unperturbed control (n=13, blue) over time. Red arrow shows the timepoint of administration of PD0325901 and IWP-2 for the perturbed organoids. Solid lines: mean, shaded areas: standard error. (C) Bar graph of somite segment sizes in organoids treated with PD0325901 (1μM, n=5), IWP-2 (2μM, n=4), and unperturbed control (n=9). Bars represent the mean; whiskers represent the standard deviation. Black dots represent individual organoids. (D) Length fold change (left), presomitic mesoderm length fold change (middle), and somitic mesoderm length (right) as a function of time in organoids treated CHIR (n=16, green) and unperturbed control (n=16, blue). Red arrow shows the timepoint of administration of CHIR for the perturbed organoids. Solid lines: mean, shaded areas: standard error. (E and F) Confocal images of control (E) and CHIR treated (F) Typical images of organoids stained for DAPI, epithelial marker ZO-1, and somite marker MESP2, show MESP2 expression pattern resolved into an alternating pattern in each segment (one segment marked with white arrow) and segmented epithelial somites (ZO-1 puncta in one individual somite marked with white arrow). The CHIR-treated organoid is substantially longer than control. Scale bar, 200μm (G) Length fold change (left), presomitic mesoderm length fold change (middle), somitic mesoderm length (right) as a function of time in organoids treated with FGF4 (n=9, red) and unperturbed control (n=13, blue). Red arrow shows the timepoint of administration of FGF4 for the perturbed organoids. Solid lines: mean, shaded areas: standard error. (H) Typical image of an FGF4-treated organoid stained for DAPI, epithelial marker ZO-1, and somite marker MESP2. In contrast with control organoids in (E), FGF4-treated organoids do not show segmentation and no ZO-1 puncta associated with epithelial somites. Scale bar, 200μm.

Conversely, experiments in mouse have indicated that WNT plays a role in defining the position of the determination front¹⁴. These results were obtained in mice through β-catenin deletion or stabilization. Unlike experiments in organoids or zebrafish^49,50, where the perturbation can be carefully timed, the effects of these mutations last throughout development, making it difficult to distinguish direct from indirect effects. Indeed, levels of FGF ligand and signaling activity were also significantly affected in these mutants, making it difficult to disentangle the effects of WNT perturbations from the downstream effects through FGF. Therefore, we next tested the role of FGF signaling in axial morphogenesis.

Consistent with studies in chick¹³ and zebrafish⁵¹ embryos, FGF inhibition in the organoids using FGF/ERK inhibitor PD0325901 (1μM) led to truncation, with both the total organoid length and PSM length being shorter than control (Fig 4, A and B, Fig. S5A). FGF inhibition further led to an accelerating somite determination front propagation, and somite segments were about twice as large as control organoids (Fig. 4C, Fig. S5A Movie S2). To observe the effects of FGF activation during somitogenesis, we exposed organoids to FGF4 (100 ng/mL) ligand at 96 h of differentiation. Uniform FGF4 treatment transiently decreased the size of the PSM. The truncation of the organoid compared to control is eventually due to the shortening of the somitic mesoderm. This suggests that a gradient of FGF activity is required for elongation, consistent with the literature.^9,11,52–54 (Fig. 4G, Fig. S5D). FGF4-treated organoids had a decelerated determination front progression (Fig. 4G) and disrupted somite segmentation, as seen by the lack of ZO-1 foci or segments in the perturbed organoids (Fig. 4H, Fig. S5E). By performing β-catenin and dpERK immunostaining on the organoids treated with CHIR and FGF4, we validated that there was no cross-activation between WNT and FGF pathways after exposure for one oscillation period (4.5 hours) (Fig S5, F, G, and H).

These results indicate that while both FGF and WNT pathways are important for the axial elongation of both the neural tube²⁵ and the mesoderm, the FGF pathway additionally plays a direct role in the definition of the somite determination front and the segmentation of the somites.

FGF4 gradients are required for the propagation of segmentation clock waves

How waves of gene expression travel anteriorly along the presomitic mesoderm remains unknown¹⁷. Furthermore, we do not know how the waves interact with the FGF and WNT signaling gradients. To determine if diffusible signaling gradients played a role in the propagation of segmentation clock waves, we wanted to place isolated colonies of PSM cells at a distance from each other to determine whether they could still communicate and mutually coordinate their segmentation clock oscillations through diffusive signals. Our logic was that if, in any configuration of these colonies that were not physically in contact, we could see coherent wave propagation across the colonies, it would suggest a role for diffusive molecules in the spatial coordination of the segmentation clock. We, therefore, performed the experiments for different spatial configurations of colonies, from those with uniform spacing between the colonies to those with a gradient of colony density. To achieve this, we micropatterned pluripotent stem cell colonies in proximity to each other on a coverslip and constrained colony expansion and cell migration by passivating the coverslip surface (Fig. 5A, Fig. S6, A, and B). The colonies could not touch each other, preventing communication between colonies through juxtacrine signaling (such as through NOTCH or YAP). By treating cells with CHIR and LDN for 48 hours, we differentiated colonies to a presomitic mesoderm identity. At the end of 48 hours, we replaced differentiation media with basal media and recorded HES7 oscillations (Fig. 5A, Fig. S6A). If diffusible signals did not play a role in generating traveling waves, we expected not to see a phase gradient across the colonies and, concomitantly, no propagation of NOTCH activity waves sweeping coherently across the colonies. In uniformly spaced colonies, time-lapse imaging revealed that the HES7 oscillations were synchronous (Fig. S6F). Contrarily, HES7 oscillations were spatially coordinated between the microprinted colonies in the patterns that had a radial density gradient (inter-colony distance increases with the distance from the center), and a phase gradient of HES7 oscillations was established, resulting in HES7 waves propagating from colonies at the edge to those in the center of the pattern (Fig. 5A–C, Figure S6A, Movie S3). These results show that when colonies that are not in contact are arranged appropriately in space, their oscillation dynamics are coupled, leading to waves that travel across the colonies. Thus, diffusible signals could be important for the propagation of segmentation clock waves.

Fig.5. FGF gradient is required for HES7 traveling expression waves and somite segmentation.

(A) Stills from time-lapse imaging PSM colonies on microcontact printed arrays with HES7 expression reporter. Detrended HES7 signal averaged over each colony is represented by green color intensity. Scale bar, 500 μm. (B) Colonies colored by their oscillation phase. Scale bar, 500 μm. (C) Plot showing oscillation phase of each colony and its distance from the center of the array. Black dots represent individual colonies. Solid line: mean, shaded area: standard deviation. Positive slope of the line indicates waves traveling from edge to inside of the array. (D) Bar graph of oscillations of HES7 amplitude of organoids treated with IWP-2 (2μM, n=3), DAPT (25μM, n=4), PD0325901 (1μM, n=5), and unperturbed control (n=15). Amplitude of the oscillations was calculated by normalizing the amplitude of 4^th peak after the treatment by the amplitude of 1^st peak after the treatment. Bars represent the mean; whiskers represent the standard deviation. Black dots represent individual organoids. (E) Stills from time-lapse imaging of organoids with HES7 (green) and MESP2 (red) expression reporters for (Top: Unperturbed Control, bottom: FGF4 addition). Time interval between images is 15 min. Scale bar, 100 μm. (F) Plots showing the phase profile of the organoids treated with FGF4 (left) and CHIR (right) compared to unperturbed control organoids (see Methods). Lines represent mean and shaded area represents standard deviation over (Left: FGF4, n=9; Control, n=14, right: CHIR, n=10; Control, n=9) biologically independent replicates. (G) Plot showing the oscillation period profile of the organoids treated with FGF4 (red) compared to unperturbed control (blue) organoids (see Methods). Lines represent mean and shaded area represents standard deviation over (FGF4, n=9; Control, n=14) biologically independent replicates. (H) (Top left) Kymograph of NOTCH activity in control (unperturbed) PSM generated by the numerical simulation of a simple mathematical model shows anteriorly propagating HES7 waves (green), MESP2 (red) expression (compare with Fig 3C). (Bottom left) Snapshots from the same simulation of the PSM, at consecutive time points, show anteriorly propagating NOTCH waves (green) and posteriorly moving somite front (red), consistent with the kymograph. (Top right) Numerical simulation results for the length of the somitic mesoderm in unperturbed and FGF-treated models are shown. FGF treatment slows the determination front propagation, consistent with the experiments. (Bottom right) Snapshot from the numerical simulations of the PSM at consecutive time points, in which FGF signaling was stimulated at 25hrs. HES7 (green) and MESP2 (red). FGF treatment results in loss of segmentation clock waves, synchronous oscillations through PSM, decelerated somite determination front, and somite polarity defects. (I) Proposed mechanism for A-P patterning of paraxial mesoderm wherein FGF gradient controls wave propagation, somite segmentation, and determination front propagation while FGF and WNT together control axial elongation.

We, therefore, investigated whether FGF and WNT signaling could modulate the propagation of the measured HES7 waves in organoids. We observed that FGF inhibition resulted in the downregulation of the amplitude of HES7 oscillations. In contrast, WNT inhibition did not affect the oscillations (Fig. 5D), indicating that the FGF pathway is not only involved in defining the somite determination front and regulating somite segmentation but also in regulating the segmentation clock. We next uniformly activated FGF and WNT pathways in organoids. Time-lapse imaging of organoids revealed that uniformly activating the WNT pathway by adding CHIR did not affect the phase gradient along the A-P axis compared to the control organoids (Fig. 5E and F, Fig. S6, C and D, Movie S4), showing that the WNT pathway has no direct effects on the dynamics of the segmentation clock. Treating organoids with FGF4 ligand resulted in synchronization of the oscillations throughout the A-P axis and loss of the traveling waves. In contrast, in control organoids, the segmentation clock waves propagated anteriorly through the PSM (Fig 5, E and F, Fig. S6E, Movie S4). Further, FGF4 addition accelerated the oscillations anteriorly, resulting in anterior and posterior PSM to oscillate with the same period (Fig. 5G). Similarly, adding FGF4 to microprinted colonies accelerated oscillations and abolished the traveling waves (Fig. S6G). Thus, we concluded that the FGF signaling gradient drives the propagation of segmentation clock waves during human somitogenesis through frequency modulation.

Discussion

In physical systems that break symmetry, coupling the underlying degrees of freedom can substantially reduce the entropy of the broken symmetry state. Demonstrating the power of the approach developed in Anand et al., our study shows that by similarly coupling organoids, one can reduce the entropy of the broken symmetry state to obtain robust differentiation. The resulting axial organoids recapitulate critical aspects of axial development, including axial elongation, single-lumen neural tube formation, traveling segmentation clock waves, and sequential somite segmentation. These organoids allow us to image and deliver perturbations with temporal precision and at timescales corresponding to the clock oscillation times to extract mechanistic insight. Such an ability will enable us to study mammalian, specifically human axial development and associated diseases.

The accessibility of the organoids allowed live imaging, which is challenging in vivo in mouse, and impossible in human. Interpreting the effects of in vivo genetic perturbations is also challenging as the readouts of these perturbations are often indirect. In contrast, timed perturbations and simultaneous measurements of signaling pathway activity are easily achieved in organoid systems. In conjunction with the reproducibility of our organoids, such an ability is essential for achieving the reported results. Together, the experiments enabled us to obtain three significant insights about axial patterning and morphogenesis. First, we showed that WNT and FGF pathways together drive axial elongation. The absence of either of these signaling pathways leads to axis truncation. Moreover, unlike the WNT pathway, uniform activation of the FGF pathway also leads to axis truncation, highlighting the requirement of an FGF gradient for axial elongation. Second, by observing the immediate changes in determination front position upon temporally controlled inhibition of the FGF and WNT pathways, we could disentangle the roles of these two pathways in axial extension and somite patterning. We showed that the position of the determination front is determined solely by FGF and not by WNT signal. Third, we showed that the FGF signaling gradient along the A-P axis drives segmentation clock waves by modulating the period of the NOTCH oscillations at the cellular level. Posterior to anterior FGF activity gradient thus generates a frequency and phase gradient along this axis, leading to anteriorly traveling segmentation clock waves. Consequently, uniform activation of the FGF pathway results in synchronous oscillations throughout the A-P axis and a loss of traveling segmentation clock waves by accelerating the oscillations anteriorly. A simple mathematical model in which the level of FGF pathway activity determines both the oscillation frequency of the NOTCH targets and the determination front position is sufficient to produce anteriorly traveling clock waves, posteriorly moving determination front, and anteroposteriorly polarized somite segmentation (Fig 5H, see Methods). Thus, the FGF pathway plays a central role in orchestrating the dynamics of axial patterning and morphogenesis in humans (Fig 5I).

Limitations of the Study:

While we demonstrated the robustness of our approach in vitro, how symmetry is broken robustly in vivo remains an open question. One speculation is that the signals that the coupled organoids secrete to break symmetry coherently are secreted in vivo by the surrounding tissues with the appropriate spatial profiles. Our research exploited the robust in vitro system to study axial elongation and patterning. We also note that the mathematical model is for illustrative purposes only, given the lack of knowledge of most parameters for a more detailed model. We intended to show how signaling gradient-driven traveling waves and moving somite determination front are possible in such simple models. The experiments on humans necessarily involve in vitro systems. Comparisons to other mammals, in the case of conserved features, will be necessary to address the in vivo relevance of these results. Lastly, we have used the word “organoid” throughout this paper to describe an organized aggregate of stem cell derivatives that undergo morphogenesis. While a term like “organized stem cell-derived aggregate” is more accurate, we use organoid as it has been routinely used as such in the literature.

STAR METHODS

RESOURCE AVAILABILITY

Lead Contact

Further information and requests for resources and reagents should be directed to and will be fulfilled by the lead contact, Sharad Ramanathan (sharad@cgr.harvard.edu).

Materials Availability

This study did not generate new unique reagents.

Data and Code Availability

• Single-cell RNA-seq data have been deposited at GEO and are publicly available as of the date of publication. Accession numbers are listed in the key resources table. Microscopy data reported in this paper will be shared by the lead contact upon request.

• All original code has been deposited at Zenodo and is publicly available as of the date of publication. DOIs are listed in the key resources table.

• Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.

KEY RESOURCES TABLE

REAGENT or RESOURCE	SOURCE	IDENTIFIER
Antibodies
Rat Monoclonal Anti-SOX2	Thermo Fisher Scientific	RRID:AB_11219471
Mouse Monoclonal Anti-ZO1	Thermo Fisher Scientific	RRID:AB_2532187
Goat Polyclonal Anti-SOX1	R and D Systems	RRID:AB_2239879
Goat Polyclonal Anti-Brachyury	R and D Systems	RRID:AB_2200235
Goat Polyclonal Anti-TBX6	R and D Systems	RRID:AB_2200834
Mouse Monoclonal Anti-PAX6	BD Biosciences	RRID:AB_10715442
Mouse Monoclonal Anti-β-Catenin	BD Biosciences	RRID:AB_397554
Rabbit Monoclonal Anti-N-Cadherin	Cell Signaling Technology	RRID:AB_2687616
Rabbit Polyclonal Pan p44/42 MAPK (phosphorylated Erk1/2)	Cell Signaling Technology	RRID:AB_331646
Chemicals, Peptides, and Recombinant Proteins
mTeSR™ Plus	StemCell Technologies	5825
ReLeSR	StemCell Technologies	5872
TeSR™-E6	StemCell Technologies	05946
Matrigel hESC-qualified Matrix, *LDEV-Free	Corning	354277
Heparin sodium salt from porcine intestinal mucosa	Millipore	H3393–100KU
CHIR-99021	Selleck Chemicals	S2924
PD0325901	Selleck Chemicals	S1036
N-2 Supplement	Thermo Fisher Scientific	17502048
B-27™ Supplement (50X), minus vitamin A	Thermo Fisher Scientific	12587010
LDN 193189 dihydrochloride	R and D Systems	6053/10
Penicillin-Streptomycin	Millipore	P4458
rhFGF4	R and D Systems	235-F4–025
DMEM/F-12, HEPES, no phenol red	Thermo Fisher Scientific	11039021
GlutaMAX™ Supplement	Thermo Fisher Scientific	35050061
Insulin-Transferrin-Selenium (ITS - G) (100X)	Thermo Fisher Scientific	41400045
MEM Non-Essential Amino Acids Solution (100X)	Thermo Fisher Scientific	11140050
2-Mercaptoethanol	Thermo Fisher Scientific	21985023
Bovine Serum Albumin solution	Millipore	A9576
Deposited Data
Single cell RNA-seq data	This study	NCBI GEO: GSE220563
Single cell RNA-seq data	Diaz-Cuadros et al.18	NCBI GEO: GSE114186
Experimental Models: Cell Lines
HES7-Achilles;MESP2-mCherry iPSC line	Laboratory of Olivier Pourquié	N/A
Software and Algorithms
Zen	Zeiss	https://www.zeiss.com/microscopy/en/products/software/zeiss-zen.html
Fiji/ImageJ	Schindelin et al.56	https://imagej.net/software/fiji/
Arivis Vision4D	Arivis	https://www.arivis.com/
ilastik	Berg et al.57	https://www.ilastik.org/index.html
MATLAB	MathWorks	https://www.mathworks.com/products/matlab.html
MOrgAna	Gritti et al.58	https://github.com/LabTrivedi/MOrgAna
Scanpy	Wolf et al.59	https://scanpy.readthedocs.io/en/stable/
Scripts used for analyzing kymographs, scRNA-seq and script for mathematical model	This paper	https://doi.org/10.5281/zenodo.7458178

EXPERIMENTAL MODELS AND SUBJECT DETAILS

Cell lines

All experiments were conducted using NCRM1 iPS cells with endogenous locus of HES7 tagged with Achilles and MESP2 tagged with mCherry (provided generously by the Pourquie Lab). Sex is not a relevant parameter for this study. iPSCs were cultured in 6-well tissue culture dishes treated for 1 hour with 1X diluted Matrigel (Corning) and supplied with mTeSR Plus media (STEMCELL Technologies). Media is changed with fresh media every two days. For routine culture, we passaged by washing with Dulbecco’s phosphate buffered saline (DPBS) followed by ReLeSR (STEMCELL Technologies) treatment. Briefly, cells after washing with DPBS, cells are treated with ReLeSR for 30 seconds. Then ReLeSR is aspirated and cells are incubated in the incubation chamber (37 °C, 5%CO₂) for 5 minutes. Cells are rescued using 1 ml of mTeSR Plus. 25 μl of the cell suspension is added to a well of a 6-well plate coated with Matrigel. All cell lines used were routinely tested for mycoplasma contamination (Mycoplasma PCR Detection Kit, ABM Cat. No. G238). We used hiPSCs in accordance with approvals by Harvard University IRB (protocol #IRB18- 0665) and Harvard University ESCRO (protocol E00065).

METHOD DETAILS

Microfabrication and Soft Lithography

Briefly, round ADEX-50 dry film photoresist films (DJ Microlaminates) were laminated onto round 76.2 mm Si wafers (University Wafers) at 65°C using a SKY laminator. Films were exposed through 8 μm-resolution photomasks (CAD/Art Services) to 365 nm UV light at an intensity of 25 mW/cm^2 for 13 seconds using a UV lamp (Uvitron), baked at 80°C for 15 minutes, and developed face down in cyclohexanone on a steel mesh without shaking for 5 minutes, followed by washing with acetone and isopropyl alcohol and drying with compressed air. Afterwards, masters were hard-baked on a hot plate at 200°C for 1 hour and silanized for 1 hour in a vacuum chamber with 50 μl of trichloro(1H,1H,2H,2H-perfluorooctyl) silane. To cast PDMS, the elastomer base and curing agent (Dow SYLGARD^™ 184, Ellsworth Adhesives) were mixed at a ratio of 1:9, degassed, poured onto masters, and baked at 80°C for 1 hour. Stamps were covered with Scotch tape to prevent dust accumulation and cut using a scalpel.

Glass Micropatterning

PDMS stamps were treated with 1X Matrigel overnight at room temperature. Stamps were washed with MilliQ water and dried using pressurized air. Stamps were brought into contact on the features-side to the glass coverslips (22 mm No. 1.5 square borosilicate glass coverslips (VWR)) and gently pressed with a tweezer to ensure contact. Stamps were removed after 30–60 seconds, and coverslips were submerged into PBS for storage at 4°C until cell seeding.

Generation of human axial organoids

hPSC colonies on maintenance plate were washed with DPBS twice and incubated in Accutase for 10 mins in 37°C incubators. Cells were resuspended as single cells at 1.5 M/mL density in mTeSR+ containing 10 mM Y27632. Micropatterned coverslips were mounted in 6-well glass bottom plates using silicone grease. 2 mL of the suspension was pipetted onto micropatterned coverslips and incubated at 37°C incubator for 75 mins. Excess media and non-adherent cells were removed by aspiration, coverslips were washed twice with pre-warmed DPBS and replaced with mTeSR+ containing 10 mM Y27632. Cells were incubated overnight. On the following day, the media was replaced with mTeSR+ and cells were incubated overnight again. After 48 hours from initial seeding, cells formed confluent colonies on micropatterns.

The differentiation was started by adding N2B27(DMEM/F12 with 1X N2, 1X B27, 1X penicillin/streptomycin, 1% NEAA, 0.5% GlutaMAX, 0.1% ß-mercaptoethanol, and 0.05% bovine serum albumin) media containing Matrigel (6 %, v/v) supplemented with 4 mM CHIR99021 (CHIR), 0.5 mM LDN193189 (LDN) and 5mM A83–01. The time of initiation of differentiation was denoted as timepoint 0. At 48 h, organoids with a single lumen on micropatterns could be observed. At this point, the media was replaced with E6, and organoids were removed from the surface using a cell scraper. Each organoid as moved to a well of a 96-well Low Bind plate containing 100 uL E6 and incubated overnight. At 72 h, E6 containing Matrigel was added to the wells, making the final Matrigel concentration 6 % v/v. Organoids were incubated in this media for the following 48 hours. For extended incubation, additional 100 uL E6 was added to the wells.

Sample fixation and Immunostaining

Organoids were collected from 96-well plates and washed twice in DPBS before fixation in 4% PFA for 20 mins at room temperature. After the fixation, organoids were washed three times in PBS, then stored at 4°C until the blocking step. Organoids were permeabilized and blocked in PBS with 0.3% Triton X-100 and 5% Normal Donkey Serum for 60 mins at room temperature. Primary antibodies were diluted in antibody dilution buffer and incubated overnight at 4°C with gentle rocking. After the primary staining step, organoids were washed three times in PBS for 5 mins and incubated in Alexa-Fluor-conjugated secondary antibodies and DAPI diluted in antibody dilution buffer overnight at 4°C with gentle rocking. Finally, organoids were washed three times in PBS and imaged. The following primary antibodies were used at the indicated dilutions: Rat anti-SOX2 (1:400, Thermo Fisher BTJCE), Rabbit anti-NCadherin (1:400, Cell Signaling D4R1H), Mouse anti-ZO1-FITC (1:800, Thermo Fisher 1A12), Goat anti-SOX1 (1:400, R&D AF3369), Goat anti-TBXT (1:400, R&D AF2085), Goat anti-TBX6 (1:400, R&D AF4744), Mouse anti-PAX6(1:400, BD Biosciences 561462), Mouse anti-β-catenin (1:400, BD Biosciences 610153), Rabbit anti-dpERK(1:200, Cell Signaling 9101). In the immunostainings for dpERK and β-catenin, the first two wash steps were skipped, and organoids were fixed in 96-well V-bottom plate by adding certain amount of 10% PFA to the media to have organoids in 4% PFA final concentration. In the case of dpERK staining, organoids were dehydrated in cold methanol for 10 minutes at −20 °C followed by three PBS washes. The rest of the standard protocol were followed for dpERK and β-catenin immunostainings.

Hybridization Chain Reaction (HCR) of organoids

HCR was performed on organoids following the previously published protocol⁵⁵. Briefly, organoids were fixed in 2% formaldehyde overnight. The next day, organoids were washed 2 times with PBST (0.1% Tween20 in 1xPBS) for 5 minutes and dehydrated with a series of graded methanol washes with 25%, 50%, 75%, and two times 100% methanol in PBST, 5 minutes for each wash. Samples were incubated overnight or until use at −20 °C. The next day, samples were rehydrated through a series of graded methanol washes with 100%, 75%, 50%, and 25% methanol in PBST and two times with 100% PBST for 5 minutes each. Samples were treated with 25 ug/mL proteinase K for 4 minutes at room temperature and washed twice with PBST for 5 minutes each. Samples were refixed in 4% formaldehyde for 20 minutes at room temperature, then washed 3 times with PBST. Later, samples were washed with prewarmed PH buffer at 37 °C for 5 minutes. After the wash, samples were resuspended in PH buffer and incubated for 30 minutes at 37 °C. Samples were incubated in 500 uL of PH buffer along with 4 pmol of the probe mixture overnight. On the next day, hairpin mixtures were prepared by bringing h1 and h2 of each hairpin to 95 °C for 90 seconds and leaving it at room temperature for 30 minutes. Two hairpin mixtures are then added to the amplification buffer with a final concentration of 48 pM. Samples were washed with probe wash buffer at 37 °C for four times, 15 minutes for each wash. Samples were then washed with 5xSSCT two times at room temperature, 5 minutes for each wash. Samples were washed once with amplification buffer for 5 minutes and resuspended in the hairpin mixture, incubated overnight at room temperature. On the final day, organoids were washed with 5x SSCT for 30 minutes at room temperature and nuclei were stained with washing organoids in the 1:1000 DAPI (2 μg/mL) three times, 25 minutes for each wash. Finally, samples were washed two times for 15 minutes with 5xSSCT at room temperature and imaged. HCR probe design was: FGF4 (Accession NM_002007), FGF8 (Accession NM_033163), WNT3A (Accession NM_033131), CYP26A1 (Accession NM_057157), ALDH1A2 (Accession NM_170697).

Wide-field microscopy

Axial organoids at 72h, 96h and 120h stage were imaged using a Zeiss AxioObserver Z1 inverted microscope in a humidified incubator (5 % CO2, 37 °C), with a Zeiss EC Plan-Neofluar 10x/0.30 NA objective. The 43 HE DsRed/46 HE YFP/47 HE CFP/49 DAPI/50 Cy5 filter sets from Zeiss were used. Images were acquired using an Orca-Flash 4.0 CMOS camera (Hamamatsu). The microscope was controlled using ZEN software. All images were analyzed using Fiji⁵⁶, Ilastik⁵⁷, MATLAB, Morgana⁵⁸ or Python.

Confocal imaging of fixed and live samples

Fixed samples were imaged on a Zeiss LSM 980 with Airyscan using a Zeiss 10x (NA 0.45) objective. Detection was performed on DAPI, AlexaFluor 488, AlexaFluor 568 and AlexaFluor 647 channels. A Z-stack with 1-micron intervals was acquired from the lower to upper apical surface of each organoid. After Airyscan processing, a maximum Z intensity projection was performed for visualization purposes. Nuclear segmentation is done and analyzed by using Arivis Vision4D.

Time-lapse imaging of organoids

For time-lapse imaging of organoids, the method described in generation of human axial organoids was followed until 70 hours of differentiation. Later, organoids were collected in a 5 mL Eppendorf tube and centrifuged at 200 rcf for 1 minute. Supernatant was removed and organoids were suspended in 2 mL of basal media DGIP (DMEM F-12 no phenol red, Glutamax, Insulin-Transferrin-Selenium, Penicillin-Streptomycin). Organoids were then transferred to 96-well glass bottom plates along with 10 uL of DGIP for each organoid, each well containing 50 uL of DGIP. Following the transfer of the organoids, 50 uL of ice cold DGIP containing 12 % v/v Matrigel was added to each well, resulting 6 % v/v final Matrigel concentration. The plate was then placed in humidified incubator for 2 hours, allowing the Matrigel to solidify. Later, the plate was moved to Zeiss AxioObserver Z1 inverted microscope in a humidified incubator (5 % CO2, 37 °C) and imaging was started immediately. Imaging was done using a Zeiss EC Plan-Neofluar 10x/0.30 NA objective. Images were taken every 15 min. The 43 HE DsRed/46 HE YFP filter sets from Zeiss were used. Images were acquired using an Orca-Flash 4.0 CMOS camera (Hamamatsu) with 2×2 binning. For perturbations, timelapse was paused and 20 uL of DGIP containing the respective small molecules or recombinant proteins without removing the culturing plate from the stage. In all perturbations with FGF4 ligand, the media is supplemented with 1 μg/ml heparin (Sigma Aldrich cat. no. H3393–100KU) The microscope was controlled using ZEN software.

Micropatterning, passivation of glass coverslips and time-lapse of micropatterned colonies

PDMS stamps were treated with 1X Matrigel overnight at room temperature. Stamps were washed with MilliQ water and dried using pressurized air. Stamps were brought into contact on the features-side to the plasma treated glass coverslips (22 mm No. 1.5 square borosilicate glass coverslips (VWR)) and gently pressed with a tweezer to ensure contact. 0.1 mg/ml PLL-g-PEG buffered with 10 mM HEPES was flown between the stamp and the coverslip surface and incubated for 30 min before removing the stamp. The coverslips were washed three times with PBS and the stamp was removed. hPSC colonies on maintenance plate were washed with DPBS twice and incubated in Accutase for 10 mins in 37°C incubators. Cells were resuspended as single cells at 1.5 M/mL density in mTeSR+ containing 10 mM Y27632. Micropatterned coverslips were mounted in 6-well glass bottom plates using silicone grease. 2 mL of the suspension was pipetted onto micropatterned coverslips and incubated at 37°C incubator for 75 mins. Excess media and non-adherent cells were removed by aspiration, coverslips were washed twice with pre-warmed DPBS and replaced with mTeSR+ containing 10 mM Y27632. Cells were incubated overnight. On the following day, the media was replaced with mTeSR+ and cells were incubated overnight again. After 48 hours from initial seeding, cells formed confluent colonies on micropatterns. The differentiation was started by adding N2B27(DMEM/F12 with 1X N2, 1X B27, 1X penicillin/streptomycin, 1% NEAA, 0.5% GlutaMAX, 0.1% ß-mercaptoethanol, and 0.05% bovine serum albumin) media containing Matrigel (6 %, v/v) supplemented with 4 mM CHIR99021 (CHIR), 0.5 mM LDN193189 (LDN). The time of initiation of differentiation was denoted as timepoint 0. At 48 hours of differentiation, the plate was moved to Zeiss AxioObserver Z1 inverted microscope in a humidified incubator (5 % CO2, 37 °C) and imaging was started immediately. In the case of FGF4 perturbation, FGF4 was added to the media right before the imaging started. Imaging was done using a Zeiss EC Plan-Neofluar 20x/0.50 NA objective. Images were taken every 15 min. The 46 HE YFP filter sets from Zeiss were used. Images were acquired using an Orca-Flash 4.0 CMOS camera (Hamamatsu) with 2×2 binning.

Single-cell RNA sequencing

Organoids were dissociated into a single-cell suspension using the Worthington Papain Dissociation System kit (Worthington Biochemical). Cells were counted on the LUNA-FX7 Automated Cell Counter (Logos Biosystems) using fluorescence detection for viability with an acridine orange/propidium iodide stain (Part No. F23011). After counting, the sample was loaded into Chip G per the user guide from 10x Genomics, and no alterations were made at any step of the protocol (Part No. CG000315). GEMs were formed targeting 10,000 cells and reverse transcription completed immediately after. The cDNA was cleaned from the GEM reagents, amplified for a total of 11 cycles and verified via TapeStation (Agilent Technologies). Amplified cDNA was diluted and ran on the 4200 TapeStation instrument using High Sensitivity D5000 tape and reagents (Part No. 5067–5592 & 5067–5593). The amplified cDNA was fragmented, end repaired, and A-tailed followed by adaptor ligation, and PCR amplification for a total of 11 cycles with each sample receiving a unique set of dual indices (Part No. 1000215). Final libraries were diluted and ran using the High Sensitivity D5000 tape and reagents (Part No. 5067–5592 & 5067–5593) on the 4200 TapeStation (Agilent Technologies). Libraries were quantified via Kapa qPCR using the Complete Universal Kit (Part No. 07960140001, Roche Sequencing Solutions) and the CFX96 Touch Real-Time PCR Detection System (Bio-Rad Laboratories). Libraries were sequenced on an Illumina NovaSeq instrument using the parameters outlined in the user guide (Read1: 28 bp, i7 index: 10 bp, i5 index: 10 bp, Read2: 90 bp). After sequencing and demultiplexing, the Cell Ranger count pipeline to align reads to the GRCh38 human reference genome and produce the associated cell by gene count matrix.

Processing of scRNA-seq data

Cells with 6,000 to 30,000 reads were subsampled to a obtain a read count of 6,000 for each cell. Sparse multimodal decomposition (SMD)¹⁸ was performed in Python on the subsampled count matrix. Top 150 genes with a highest z-score from SMD were filtered to remove genes with a log normalized expression mean or standard deviation less than 0.05, genes expressed in more than 90% or less than 1% of cells, and genes associated with the cell cycle, resulting in a list of 48 genes. In the subspace of these 48 genes, cells were hierarchically clustered, and 6 clusters were identified. Clusters were annotated manually based on differentially expressed genes. UMAP plots were generated using ScanPy⁵⁹.

Diffusion map analysis was performed using the DPT method¹⁹ in scanpy in the subspace of 48 genes. The root cell was selected to be a cell from the NMP cluster with the highest value along the first principal component from principal component analysis. To generate a pseudo-spatial gene expression heatmap, cells were ordered by pseudo-spatial index and their z-score normalized gene expression values were smoothed using a Gaussian filter with a kernel size of 50 for mesodermal clusters and 150 for neural clusters. Top 200 differentially expressed genes were selected for mesodermal and neural clusters, based on the difference of the highest and the lowest values of z-score normalized gene expression on respective clusters. Genes were then ordered by the pseudo-spatial position of their peaks of smoothed gene expression values.

To generate pseudo-spatial gene expression plots for individual genes, a moving average filter was applied to log-normalized gene expression values on the pseudo-spatial axis was applied to mesodermal and neural branches with an averaging width of 201 cells for mesodermal clusters and 601 for neural clusters. Later, each gene expression was normalized based on the highest expression of the gene on the respective lineage.

Comparison of Cell Types with in vivo Mouse Cells

To pre-process the mouse data set, we selected cells belonging to neural and paraxial mesodermal lineages in the mouse dataset. From this subset of cells, we removed doublets and cells with low read counts by selecting cells that had between 8000 and 12000 reads. We then normalized the read counts from each cell both in the mouse and human datasets. After log normalizing each dataset, we combined them (before which we found the corresponding homologous genes between mouse and human to map the mouse genes onto human genes). The resulting dataset consisted of 2376 mouse cells and 9096 human cells with reads from 7989 genes. From these genes we selected only the genes that had a high Z score (Z>1.5, 48 top genes) to reduce the gene expression space to those that were detected to be bimodally expressed. In this subspace, we performed hierarchical clustering, and found that cells belonging to the same cell identity clustered together (Fig S3A). The cells from human and mouse were intermixed. Further, we annotated the cell types using marker gene expressions. We found that except neural progenitor cell type and mature somites, all cell types identified in the human dataset were present in the mouse tail bud. The absence of neural progenitors and mature somites in the mouse dataset was because these tissues are more anterior to the tail bud both in the embryo and in our organoids, therefore tail bud explant used for the single cell RNA sequencing did not contain these tissues in mouse. To visualize the cell types, we performed principal component analysis and plotted the cells in the first two principal component subspace (Fig S3B).

Later, we isolated the cells belong to common cell types between these two datasets, namely Neuromesodermal Progenitors, Presomitic Mesoderm, Early Somite and Pre-Neural Tube. We looked for the highly differentially expressed genes in each cell type compared to the other cell types (Fig S3C). By plotting the mouse and human cells in each cell type separately, we saw that the marker gene expressions were similar between these two species, validating that the mouse equivalent cell types of the cells in our organoids are present in mouse embryos (Fig S3D).

We observed that the marker genes for NMP’s are found to be mostly signaling molecules, consistent with the fact that NMP’s are the signaling center that drives axial elongation and anteroposterior patterning⁶⁰. Therefore, we found the highly expressed FGF and WNT ligands in NMP’s for both human and mouse cells and compared them to the other tissues. This analysis showed that WNT3A is specifically expressed in neuromesodermal progenitors and presomitic mesoderm cells in both human and mouse cells (Fig S3E), which also explains the absence of canonical WNT ligands in the organoids of our companion paper²⁵ due to the absence of NMP’s and presomitic mesoderm cells.

Simulations

For illustration, we posited a straightforward mathematical model based on our measurements to demonstrate how gradients of the diffusive FGF signals can drive anteriorly moving oscillations along the PSM. Most biochemical parameters are not known for human cells, so a detailed model is impossible. We extracted effective parameters for our model from our experiments and again emphasize that this model is for illustrating the idea and showing how simple models based on our assumptions show qualitatively similar dynamic behaviors to the organoids.

Our simulation consisted of n=110 cells initially, arranged along a line in one dimension. Each cell was 5 μm long. Thus, we set the initial length of the undifferentiated PSM tissue to be 550 μm long. We assumed that each cell had an internal oscillator with a base period of 300 min based on the experimentally measured period at the most anterior end of the PSM. Based on our experimental observation, the internal oscillator was assumed to be accelerated by the cell’s FG activity (Fig. 5G, S6G). We assumed FGF profile is a function of distance from the posterior tip, x;

$$FGF(x)=FG{F}_0\left(1-\text{exp}\left(-\frac{x}{l_{\mathit{\text{FGF}}}}\right)\right)$$

where l_FGF = 300μm, estimated by dpERK measurements in Fig S2M. Here FGF₀ was used to define a dimensionless variable and set it to the maximum level of FGF(x).

Next we defined a short range retinoic acid signaling, described by the function:

$$RA(x^{\prime })=R{A}_0\mathit{\text{exp}}\left(-\frac{x^{\prime }}{l_{RA}}\right)$$

where x′ is the distance of a cell with presomitic mesoderm identity from the somite determination front, since retinoic acid is produced by somite cells, where RA₀ is a dimensionless variable and was set to 100, and l_RA was set to 10 μm. Given that retinoic acid inhibits FGF activity^49,61, we modified the FGF profile with an inhibitory retinoic acid term to define the FGF activity. Therefore FGF activity at a distance from posterior tip, x, and from the somites, x′, is defined as:

$$FG{F}_{\mathit{\text{activity}}}=\frac{\mathit{\text{FGF}}(x)}{RA(x^{\prime })+1}$$

By using the measured FGF activity profile along the A-P axis (from Fig S2M) and the measured frequency profile along the same axis (Fig. 3E), we inferred the function that maps the frequency of oscillation as a function of FGF activation:

$$\omega (\mathit{\text{FGF}})=1.391-2.619\mathit{\text{exp}}(-14.94*\mathit{\text{FGF}}/FG{F}_0)\mathit{\text{rad}}/hr$$

We modeled the growth of the organoid by cell division at the posterior tip. In the simplest model, we assumed this division rate to be constant and set it to 2.28 divisions an hour by using the measured growth rate in Fig 4A. Below a threshold activity level of FGF, we postulated that the presomitic mesoderm would differentiate into somite cells. We calculated this activity level by using the FGF activity profile function, and the mean length of the presomitic mesoderm measured in Fig 4B and set to be FGF_diff = 0.08 * FGF₀ . Cells in the model that passed this FGF threshold became somite and started expressing MESP2 when their internal oscillation phase was between (0,π/2). This assumption was to model the activation of HES7 and MESP2 simultaneously since both are the NOTCH pathway target genes⁴⁷.

External activation of the FGF pathway simulated by the FGF ligand was incorporated into the model by making the FGF activation along the entire PSM uniform and set to the maximum observed activation level, FGF₀.

Using these assumptions, we simulated the model using MATLAB. We set the initial phase of the internal oscillator to zero, therefore initial oscillations were synchronous. Over time, we observed a growing organoid with anteriorly traveling oscillations and a posteriorly moving somite determination front consistent with the experiments (Fig 5H). When we stimulated this model with uniform FGF profile by setting FGF(x) = FGF₀ at t = 25 ℎ, the entire PSM oscillated in synchrony as observed in the experiment (data not shown), and the determination front slowed down (Fig 5H), consistent with the experiment (Fig. 4G). In accordance with the two-phase model^62,63, while unperturbed control organoid, in which there are traveling HES7 waves, showed alternating MESP2 expression in a single somite segment, addition of FGF4 disrupted this alternating expression (data not shown), due to synchronous HES7 oscillations.

QUANTIFICATION AND STATISTICAL ANALYSIS

Analysis of time-lapse imaging data and generation of kymographs

Organoids were segmented using Ilastik on the phase contrast images. Fluorescence images were corrected for nonuniform illumination and autofluorescence of the media was subtracted by calculating the mean signal of the empty area for each image. Segmented organoids were rotated on the major axis and fixed on the posterior end. Signal for each pixel on the anteroposterior axis was calculated by averaging all the pixel values on the line perpendicular to the major axis on the respective position. Kymographs for HES7 and MESP2 signal were generated by using the calculated signal on the anteroposterior axis for each timepoint. For amplitude, phase, and frequency analysis, see “Quantification of phase and frequency profile on anteroposterior axis and amplitude of oscillations” section.

Length fold change was calculated by finding the length of the major axis of each organoid and dividing them to their initial length. The length of the somitic mesoderm of each organoid was calculated by manually thresholding and binarizing each MESP2 kymograph and calculating the length of the line on the space axis corresponding to each timepoint on the binarized kymograph. The length of the PSM is calculated by finding the distance from the posterior end to the position, of somite determination front, which is the most posterior position of the somitic mesoderm on the major axis. Fold change of the PSM length was calculated by dividing the PSM length at each time point by the initial PSM length for each organoid.

Segment sizes were calculated using the length of the somitic mesoderm. First, the change in the length of the somitic mesoderm between each timepoint was calculated. The timepoints corresponding to the troughs of the somitic mesoderm length change was detected. The difference of the length of the somitic mesoderm between troughs was calculated as segment sizes.

Quantification of phase and frequency profile on anteroposterior axis and amplitude of oscillations

For phase analysis, first oscillating region of each organoid was detected using HES7 kymographs by calculating the frequency with highest amplitude of the Fourier transform of the time series of each position on the anteroposterior axis. Positions with peaks between 0.21 and 0.24 h⁻¹ were considered to be oscillating around the segmentation clock frequency. After cropping the oscillating region from kymographs, we used Hilbert transform following a detrending and local renormalization algorithm, following a similar approach to a previously published algorithm⁶⁴. First, a moving average filter was applied on the space axis of kymographs with 26.66 um window. To subtract the trend in the time axis, a moving average filter with a 6-hour window was applied to the kymograph and the resulting kymograph was subtracted from the original. The time series for each anteroposterior position was then divided by a standard deviation filter with a 6-hour window. Later, phase of each position was obtained by using Hilbert transform on the time series between 38 – 43 hours of the timelapse, corresponding to 4th oscillation after the small molecule perturbations. For calculating the frequency profile on the anteroposterior axis, the change in the phase was calculated between consecutive timepoints for each position during the time-lapse, and the period was calculated using this value. The position is calculated from the anterior tip (see Methods S1).

The amplitude of the oscillations was calculated using the detrended kymographs. The mean signal was calculated for the posterior part of each organoid, corresponding between 26–133 um region from the posterior end. Peaks of the oscillations after the small molecule perturbations was detected. The signal of the fourth peak following the perturbation was normalized by the signal of the first peak following the perturbation.

Supplementary Material

1

Fig.S1 Elongating axial organoids generates neural tube with a single lumen flanked anteriorly by segmented somites and posteriorly by presomitic mesoderm, Related to Figure 1 (A) Randomly positioned organoids (top three rows) and micropatterned organoids (bottom row) in groups of four on the vertices of a square on a coverslip, each consisting of a single epithelial layer of cells enclosing a single lumen, treated with BMP inhibitor LDN193189 (0.5μM), TGFβ inhibitor A83–10 (0.5μM) and WNT agonist CHIR99021 (top to bottom: 2.5μM, 4μM, 6μM, 4 μM) for 48 hours stained for DAPI, SOX2 and TBXT. Organoids were segmented based on DAPI signal. Rightmost column shows each organoid’s position on the respective row colored by their dipole moment. Scale bar, 1mm. (B) Micropatterned organoids in groups of four on the vertices of a square on coverslips under normal differentiation conditions (LDN193189 (0.5μM), A83–10 (0.5μM) and CHIR99021 (4 μM)) for 48 hours (top) or in addition treated with the retinoic acid inhibitor AGN193109 (1 μM) for 48 hours (middle) stained for SOX2 and TBXT. Normalized histograms of dipole moments for control organoids and organoids with AGN193109 treated organoids (bottom). Retinoic acid inhibition does not affect polarization of organoids. Scale bars, 1 mm.(C) Phase contrast images overlayed with MESP2∷mCherry signal in live organoids in a 96-well low adhesion plate at 72 h (top) and 96 h (bottom) of differentiation. Scale bars, 1 mm. (D) Confocal sections of representative organoids with MESP2∷mCherry reporter on consecutive days of differentiation (72 h, 96 h, 120 h, 144 h) stained for SOX2, TBXT. SOX2 and TBXT co-expressing NMP’s reside at the posterior tip. Scale bars, 500 μm (E) Epifluorescence image of organoids with MESP2:mCherry reporter stained for paraxial mesoderm marker TBX6 at 120h of differentiation. Scale bars: 500μm. (F) Confocal sections of an organoid from with MESP2∷mCherry reporter from (top) determination front and (bottom) posterior tip at 120 h of differentiation stained for TBX6. TBX6 and MESP2 expressing cells forms a clear boundary at the determination front. Scale bars, 100 μm. (G) Epifluorescence image of organoids with MESP2:mCherry reporter stained for neural marker SOX2 and N-Cadherin (CDH2) which is condensed at the apical side of epithelial cells. All organoids have a neural tube flanked by segmented epithelialized somites. Scale bars, 1 mm. (H) Maximum intensity projection from confocal sections of an organoid with MESP2∷mCherry reporter stained for neural marker SOX2 and N-Cadherin (CDH2). Scale bars, 200μm.

2

Fig.S2 Anteroposterior organization of cell types and gene expression profiles inferred from single cell RNA-seq, Related to Figure 2 (A) Epifluorescence image of organoids with MESP2:mCherry reporter at 120h of differentiation. We performed single-cell RNA sequencing of 11009 cells obtained from these organoids after dissociation and pooling. Scale bar: 1 mm. (B) UMAP (uniform manifold approximation and projection) plots showing the log-normalized gene expression values of the genes identified by SMD. (C) Heatmap of top 10 differentially expressed genes with highest fold change for each cell type compared to the other cell types. Genes are colored by their normalized mean expression in the respective cell type. Normalization is done by scaling log-normalized expression of each gene between 0–1. (D) Heatmap of top key genes (y axis) for mesodermal (left) cell clusters (presomitic mesoderm, early somite, and somite) and neural (right) cell clusters (pre-neural tube and neural progenitors) in cells (x axis) ordered according to their inferred anteroposterior positions. Genes are ordered based on the position of their peak expression on the inferred A-P axis. Color bars on the top of heatmaps represent the cluster identity of the individual cells (same color code as in Fig. 2A). (E) Normalized posterior-anterior gene expression profiles for FGFR2 in neural clusters (top), FGFR1 in mesodermal clusters (bottom) (F) Normalized posterior-anterior gene expression profiles for secreted WNT pathway inhibitors, SFRPs in neural (top) and mesodermal (bottom) clusters. SFRP’s show high expression in the anterior for both neural and mesodermal clusters. Color bars on the top of plots represent the cluster identity of the individual cells (same color code as in Fig. 2A). (G) Normalized posterior-anterior gene expression profiles for RA pathway related genes in neural clusters (top) and mesodermal clusters (bottom) (H) Confocal sections of an organoid with MESP2∷mCherry reporter on 120 h of differentiation stained for SOX2 and PAX6. PAX6 expression is upregulated anterior to the determination front. Scale bar, 200 μm. (I) Normalized posterior-anterior gene expression profiles for NOTCH target HES5 and NOTCH ligand DLL1 in neural clusters (top left); NOTCH targets (top right), NOTCH ligands (bottom left) and NOTCH receptor (bottom right) in mesodermal clusters. Color bars on the top of plots represent the cluster identity of the individual cells (same color code as in Fig. 2A). (J) (Top left) Normalized posterior-anterior gene expression profiles for BMP ligands expressed in the mesodermal clusters. Color bars on the top of plots represent the cluster identity of the individual cells (same color code as in Fig. 2A). UMAP plots showing the log-normalized gene expression values of the genes associated with dorsal (PAX3, MSX1, IRX3, OLIG3) and ventral (PAX1) cell identities. (K) UMAP plots showing the log-normalized gene expression values of neural crest markers SOX9 and SNAI2 on neural cell clusters. (L) Confocal sections of an organoid with MESP2∷mCherry reporter stained for TBX6 and β-catenin. Nuclei were segmented based on DAPI signal and colored based on the mean nuclear β-catenin signal (left panel, bottom right). Scale bar, 200 μm. Plot of nuclear βcatenin signal along the anteroposterior axis (middle panel). Each black dot represents a nucleus. Solid line: mean, shaded area: standard deviation around mean. Plot of the distribution of TBX6+ (green) and MESP2+ (red) cells on anteroposterior axis for the organoid in the left panel (right panel). (M) Confocal sections of an organoid with MESP2∷mCherry reporter stained for TBX6 and doubly phosphorylated ERK (dpERK). Nuclei were segmented based on DAPI signal and colored based on the mean nuclear dpERK signal (left panel, bottom right). Scale bar, 200 μm. Plot of nuclear dpERK signal along the anteroposterior axis (middle panel). Each black dot represents a nucleus. Solid line: mean, shaded area: standard deviation around mean. Plot of the distribution of TBX6+ (green) and MESP2+ (red) cells on anteroposterior axis for the organoid on the left panel (right panel).

3

Fig.S3 Comparison of cell types with in vivo mouse cells, Related to Figure 2 (A) Heatmap of cell-gene matrix of human and mouse combined dataset hierarchically clustered in the high Z-score gene subspace. Blue cells: Mouse, Red cells: Human. Cell clusters are annotated by the marker gene expressions. (B) Distribution of human and mouse cells in the first two principal component of high Z-score gene subspace. Top left: Cells are colored by species. Top right: Only human cells are shown, colored by cell identity. Bottom: Only mouse cells are shown, colored by cell identity. (C and D) Matrix plot showing the marker gene expression levels for (C) cell clusters containing both human and mouse cells and (D) cell clusters containing only human or only mouse cells. (E) PCA plots showing the log-normalized gene expression values of the FGF and WNT ligands highly expressed by neuromesodermal progenitor cells.

4

Fig.S4 Dynamics of Somitogenesis and NOTCH gene expression waves in the organoids, Related to Figure 3 (A) (top left) Plot showing the time evolution of anteroposterior phase profile of the organoids in basal media, averaged over n = 53 organoids between t = 74.5 h and t = 94 h, and n = 14 organoids between t = 94 h and t = 112.5 h. Lines are colored by their corresponding time point. (top right) Box plot of the phase difference between posterior and anterior half of the organoids on 72h (n = 53), 96h (n = 52) and 120h (n = 14) of differentiation. Center line, median; box, interquartile range; whiskers, range not including outliers; ‘+’ marker symbols: outliers. (bottom) Plot showing the time evolution of anteroposterior phase profile of the organoids in basal media, averaged over n = 14 biologically independent organoids. Lines are colored by their corresponding time point. (B) Stills from time-lapse imaging of three biologically independent organoids with HES7 (green) and MESP2 (red) expression reporters. Shaded line shows the position of the determination front at the first timepoint for each organoid. A new segment of MESP2 expression appears when each HES7 wave reaches to the determination front. Time interval between consecutive images is 30 minutes. Scale bars, 200 μm. (C) Kymographs of normalized HES7 signal (left), detrended HES7 signal (middle) and sine of the detected instantaneous phase of the oscillations for 14 organoids along the anteroposterior axis of organoids from 72 h to 114.75 h of differentiation. These kymographs were used to calculate the phase profile of Control organoids in Fig. 3E. Data collected every 15 minutes. For normalization, detrending of the signal and phase detection, see Methods. (D) Kymographs showing the dynamics of HES7 (green) and MESP2 (red) expression along the anteroposterior axis of organoids from 72 h to 114.75 h of differentiation for three control organoids (left) and three organoids treated with DAPT (25 μM) at 95h (right). Data collected every 15 minutes for all plots.

5

Fig.S5 FGF drives somite determination front propagation and somite segmentation while WNT drives axial elongation, Related to Figure 4 (A) Plots of length fold change (top row), presomitic mesoderm length fold change (middle row) and somitic mesoderm length (bottom row) of organoids treated with PD0325901 (1μM, n=5, right column), IWP-2 (2μM, n=4, middle column) and unperturbed control (n=13, left column) over time. PD0325901 and IWP-2 was administered at 95.5 h for the perturbed organoids. Solid lines represent individual organoids, shaded area: standard error around mean. (B) Plots of length fold change (top row), and somitic mesoderm length (bottom row) of organoids treated with CHIR (3μM, n=16, right column) unperturbed control (n=16, left column) over time. CHIR was administered at 95.5 h for the perturbed organoids. Solid lines represent individual organoids, shaded area: standard error around mean. (C) Plot showing presomitic mesoderm length fold change of organoids treated with CHIR (3μM, n=10, right) unperturbed control (n=10, left) over time. CHIR was administered at 95.5 h for the perturbed organoids. Solid lines represent individual organoids, shaded area: standard error around mean. (D) Plots of length fold change (top left), presomitic mesoderm length fold change (bottom) and somitic mesoderm length (top right) of organoids treated with FGF4 (100 ng/mL, n=9) over time. FGF4 was administered at 95.5 h for the perturbed organoids. Solid lines represent individual organoids, shaded area: standard error around mean. (E) Confocal images of control (first two columns from left) CHIR treated (3^rd and 4^th column from left) and FGF4 treated (last two column from left) organoids at 120 h of differentiation stained for DAPI, epithelial marker ZO-1 and somite marker MESP2. Scale bar, 200μm. (F) Confocal sections of an organoid with MESP2∷mCherry reporter, treated with FGF4 (100 ng/mL, top row) and CHIR (3μM, bottom row) for 4.5 h, stained for TBX6 and β-catenin. Nuclei were segmented based on DAPI signal and colored based on the mean nuclear β-catenin signal (rightmost column). Scale bar, 200 μm. (G) Confocal sections of an organoid with MESP2∷mCherry reporter, treated with FGF4 (100 ng/mL, bottom row) and CHIR (3μM, top row) for 4.5 h, stained for TBX6 and doubly phosphorylated ERK (dpERK). Nuclei were segmented based on DAPI signal and colored based on the mean nuclear dpERK signal (rightmost column). Scale bar, 200 μm. (H) Plots of nuclear β-catenin signal (left) and nuclear dpERK signal (right) along the anteroposterior axis of organoids treated with FGF4 (100 ng/mL, green) and CHIR (3μM, blue) for 4.5 h, and unperturbed control organoids (red). Solid lines: mean, shaded areas: standard deviation around mean.

6

Fig.S6 FGF gradient is required for HES7 traveling expression waves and somite segmentation, Related to Figure 5 (A) Stills from time-lapse imaging PSM colonies on microcontact printed arrays with HES7 expression reporter. Detrended HES7 signal averaged over each colony is represented by color intensity. Scale bar, 500 μm. (B) Left: Outline of the whole microcontact printed array. Each circle represents a colony. Scale bar, 1mm. Right: Phase contrast image of the microcontact printed colonies at 48 hours of differentiation. Scale bar, 500 μm. (C–E) Kymographs of normalized HES7 signal (left), detrended HES7 signal (middle) and sine of the detected instantaneous phase of the oscillations for 9 unperturbed organoids (C) 10 organoids treated with CHIR (D) and 9 organoids treated with FGF4 (E) along the anteroposterior axis of organoids. Kymographs in (C) and (D) were used to calculate the phase profile of Control and CHIR treated organoids in Fig. 5F, right, respectively. Kymographs in (E) were used to calculate the phase profile of FGF4 treated organoids in Fig. 5F, left. Data collected every 15 minutes. (F) Left: Outline of the whole microcontact printed array with uniformly spaced colonies. Each circle represents a colony. Scale bar, 1mm. Right: Plots showing oscillation phase of each colony in the uniformly spaced colony array and its distance from the center of the array Dots represent individual colonies, lines represent mean and shaded areas represent standard deviation. (G) Plots showing oscillation phase (left) and period (right) of each colony and its distance from the center of the array for the arrays treated with FGF4 (red) and the unperturbed control (blue). Dots represent individual colonies; lines represent mean and shaded areas represent standard deviation. Period difference between r=1.2 mm and r=2.5 mm is found to be 7.5±15.8 min, which is %2.8±5.8 of one period of oscillation. Therefore, the measured period difference is insignificant in terms of traveling waves.

8

Movie S1. Timelapse imaging of 62 organoids with HES7 (green) and MESP2 (red) expression reporters, Related to Figure 3 62 organoids in basal DGIP media supplemented with 6 %v/v Matrigel, between 72–90 hours of differentiation. HES7 and MESP2 expression was overlaid on phase contrast images. Scale bar, 1 mm. Time stamp shows the time passed after onset of differentiation.

9

Movie S2. Timelapse imaging of a representative organoid with HES7 (green) and MESP2 (red) expression reporters, Related to Figure 3 and 4 (A) The organoid was imaged in basal DGIP media supplemented with 6 %v/v Matrigel, between 72–138 hours of differentiation. Time stamp shows the time passed after the differentiation was started. On the left, HES7 and MESP2 expression was overlaid on phase contrast images. Scale bar, 200 μm. Time stamp shows the time passed after the differentiation was started. (B) The organoid treated with DAPT (25μM) at 95.5 hour of differentiation. On the left, HES7 and MESP2 expression was overlaid on phase contrast images. Scale bar, 200 μm. Time stamp shows the time passed after the differentiation was started. (C) The organoid was treated with IWP-2 (2μM) at 95.5 hour of differentiation. On the left, HES7 and MESP2 expression was overlaid on phase contrast images. Scale bar, 200 μm. Time stamp shows the time passed after the differentiation was started. (D) The organoid was treated with PD0325901 (1μM) at 95.5 hour of differentiation. On the left, HES7 and MESP2 expression was overlaid on phase contrast images. Scale bar, 200 μm. Time stamp shows the time passed after the differentiation was started.

10

Movie S3. Timelapse imaging of HES7 signal from microcontact printed colonies, Related to Figure 5 Detrended and normalized HES7 expression was averaged over the colony. Scale bar, 1mm. Time stamp shows the time passed after the time-lapse started, which was at 48 hour of differentiation.

11

Movie S4. Timelapse imaging of a representative organoid with HES7 (green) and MESP2 (red) expression reporters upon WNT activation, Related to Figure 5 (A) The organoid was treated with CHIR (3μM) at 95.5 hour of differentiation. On the left, HES7 and MESP2 expression was overlaid on phase contrast images. Scale bar, 200 μm. Time stamp shows the time passed after the differentiation was started. (B) The organoid was treated with FGF4 (100 ng/mL) at 95.5 hour of differentiation. On the left, HES7 and MESP2 expression was overlaid on phase contrast images. Scale bar, 200 μm. Time stamp shows the time passed after the differentiation was started.

Highlights:

• Coupled organoids reproducibly generate neural tube, presomitic mesoderm, and somites

• Organoids display traveling clock waves, sequential segmentation during somitogenesis

• FGF and not WNT pathway determines the position of determination front

• FGF gradient drives traveling waves by modulating the frequency of HES7 oscillations