Cell-state transitions and collective cell movement generate an endoderm-like region in gastruloids

  1. Ali Hashmi
  2. Sham Tlili
  3. Pierre Perrin
  4. Molly Lowndes
  5. Hanna Peradziryi
  6. Joshua M Brickman
  7. Alfonso Martínez Arias
  8. Pierre-François Lenne  Is a corresponding author
  1. Aix-Marseille University, CNRS, UMR 7288, IBDM, Turing Center for Living Systems, France
  2. Novo Nordisk Foundation Center for Stem Cell Biology (DanStem), University of Copenhagen, Denmark
  3. Novo Nordisk Foundation Center for Stem Cell Medicine (reNEW), University of Copenhagen, Denmark
  4. Department of Genetics, University of Cambridge, United Kingdom
  5. Systems Bioengineering, DCEXS , Universidad Pompeu Fabra, ICREA, Spain

Abstract

Shaping the animal body plan is a complex process that involves the spatial organization and patterning of the different germ layers. Recent advances in live imaging have started to unravel the cellular choreography underlying this process in mammals, however, the sequence of events transforming an unpatterned cell ensemble into structured territories is largely unknown. Here, using gastruloids –3D aggregates of mouse embryonic stem cells- we study the formation of one of the three germ layers, the endoderm. We show that the endoderm is generated from an epiblast-like homogeneous state by a three-step mechanism: (i) a loss of E-cadherin mediated contacts in parts of the aggregate leading to the appearance of islands of E-cadherin expressing cells surrounded by cells devoid of E-cadherin, (ii) a separation of these two populations with islands of E-cadherin expressing cells flowing toward the aggregate tip, and (iii) their differentiation into an endoderm population. During the flow, the islands of E-cadherin expressing cells are surrounded by cells expressing T-Brachyury, reminiscent of the process occurring at the primitive streak. Consistent with recent in vivo observations, the endoderm formation in the gastruloids does not require an epithelial-to-mesenchymal transition, but rather a maintenance of an epithelial state for a subset of cells coupled with fragmentation of E-cadherin contacts in the vicinity, and a sorting process. Our data emphasize the role of signaling and tissue flows in the establishment of the body plan.

Editor's evaluation

The authors took advantage of the gastruloid system to explore mechanisms of endoderm specification at cellular resolution. First, they confirm that contrary to mesoderm, nascent endoderm does not undergo epithelial-mesenchymal transition. Second, they provide evidence for a role of tissue flow, and possibly heterogeneity of cellular junction tension, in the sorting and differentiation of the islets of endoderm cells.

https://doi.org/10.7554/eLife.59371.sa0

Introduction

Gastrulation is a crucial stage of animal development that results in the laying down of the body plan through the specification of the germ layers – the endoderm, the mesoderm, and the ectoderm – and their organization with reference to three orthogonal axes (Wolpert et al., 2006; Solnica-Krezel and Sepich, 2012; Williams and Solnica-Krezel, 2017). Defects in gastrulation result in premature death or birth defects (Ferrer-Vaquer and Hadjantonakis, 2013). In most vertebrates, gastrulation entails the reorganization of a large mass of cells that has been generated in a burst of cell divisions and the process can be easily followed and manipulated in the lab as the embryos develop externally. Mammalian embryos are different, in that an increase in the cellular mass is concomitant with gastrulation (Snow, 1977; the fact that they develop in the uterus of the mother makes this coupling and the process of gastrulation difficult to study). For this reason, our understanding of mammalian gastrulation is poor relying on mutant analysis and description of patterns of gene expression (Anderson and Ingham, 2003; Artzt, 2012). Recent live imaging of the process (McDole et al., 2018) has added an important dimension to our understanding of the event, but this is low throughput and involves time consuming analysis. Gastrulation is, essentially, a cellular process that needs to be investigated at the cellular level and it would be useful to complement the in vivo studies with alternatives in vitro.

The advent of in vitro models of mammalian development provides several advantages (Fu et al., 2021). Firstly, unlike embryos, such systems are amenable to systematic perturbations. The system size and its composition can be conveniently modulated by changing the type and the initial number of cells seeded. Secondly, environmental cues – not limited to morphogen concentration (Heemskerk et al., 2019), such as geometric confinements and properties of extracellular matrix – can be finely tuned. Lastly, such systems are amenable to live imaging at single cell resolution to follow cell fates and cell dynamics.

Gastruloids offer the opportunity to enrich our understanding of the agents that may influence gastrulation/embryogenesis – particularly the role of environment, forces, and signaling. Upon exposure to external cues and morphogens, gastruloids show an intrinsic capability to polarize, elongate and pattern in a manner that is reminiscent of the early embryo (van den Brink et al., 2014; Turner et al., 2017). Strikingly, 3D gastruloids exhibit a multiaxial organization and spatiotemporal patterning of Hox genes (Beccari et al., 2018) with signatures of somitogenesis (van den Brink et al., 2020; Veenvliet et al., 2020). From in vitro assays, it was shown that combinations of embryonic and extraembryonic stem cells is needed to generate a pro-amniotic cavity (Harrison et al., 2017) and gastrulating embryo-like structures (Sozen et al., 2018). Moreover, by exploiting aggregates, the role of mechanics – for instance a relationship between the physical contact of cells with their confinement and the expression of the mesoderm transcription factor Brachyury (T-Bra) – has been revealed (Sagy et al., 2019). Besides tridimensional (3D) systems, planar/2D gastruloids confined on micropatterns have emphasized the role of the boundary conditions, shapes (Blin et al., 2018) and scaling parameter on the patterning of the different germ layers (Warmflash et al., 2014; Etoc et al., 2016; Morgani et al., 2018; Xue et al., 2018).

However, how a genetically unpatterned and morphologically symmetric 3D ESCs aggregate transforms into a spatially organized and patterned array of germ layers is largely unknown. In particular, how cellular movements, their rearrangements and patterning coordinate has not been explored. In embryo, the widespread notion is that the endoderm is formed from a single pool of cells that firstly become mesenchymal, then migrate and a proportion of which eventually re-epithelialize (Williams et al., 2012). This notion has been recently challenged by in vivo observations that show that the definitive endoderm is formed in absence of an epithelial to mesenchymal transition (EMT) (Scheibner et al., 2021).

Here, we dissect the formation of an endoderm-like region in 3D gastruloids, focusing on the spatio-temporal deployment and cell state transitions that yield the aforesaid region; specifically, starting from an ensemble of epithelial cells, we follow the cell-state transitions that govern the mesendodermal-like progenitors by looking at expression of the transcription factor Brachyury (T-Bra) and E-cadherin (E-cad). We find that an endoderm-like region is established from a distinct pool of cells, different from the mesoderm. Furthermore, we identify tissue scale flow that localizes the progenitors of the endoderm at a pole. Lastly, we find that a heterogeneity of cellular junction tension could be responsible for segregating the endoderm-like region from the rest of the aggregate via a cell-sorting mechanism.

Results

A pole of E-cadherin expression emerges at the tip of the aggregate

To induce a pluripotent, post-implantation epiblast state of the mouse ESCs (Hayashi et al., 2011), we placed the cells in Activin and FGF throughout the protocol (Figure 1A). A portion of the aggregates were exposed to the Wnt agonist Chiron (Chi) as the combination with Activin and Chi tends to promote endoderm formation (Figure 1A; Morgani et al., 2018; Engert et al., 2013). We investigated the aggregate morphologies and gene expression patterns following a pulse of Chi (lasting a day from the second day post plating).

Figure 1 with 1 supplement see all
Signal and shape polarization of gastruloids.

(A) Schematic of the experimental protocol; mESCs seeded onto a low-adherence substrate form aggregates that are exposed to N2B27 medium, FGF and Act throughout the experiment. In addition, a pulse of Chi is provided for 24 hr - starting at 48 hr-post plating. (B) The box-whisker plot shows the distribution of elongation for Chi + (n = 37) and the control (Chi -) aggregates (n = 20) (Mann-Whitney test with correction, p-value = 3 x 10–5, N = 2 replicates). The insets delineate the contours of the two classes of aggregates. (C) Box-whisker plot showing the distribution of E-cad polarization in the Chi + (n = 37) and Chi - aggregates (n = 20). The polarization of the signal is defined by the maximum contrast between the two halves of the aggregate (Mann-Whitney test with correction, p = 7 x 10–10, N = 2 replicates). The insets display E-cad intensity within the aggregates. (D) Snapshots of aggregates (first column composed of E-cad-GFP/Oct4-mCherry and the second column composed of T-Bra-GFP/NE-mKate2 and E14Tg2a.4) exposed to Chi pulse at different developmental stages (scale bars for the columns represent 100 µm). The T-Bra-GFP/NE-mKate2 aggregate was generated from ~200 cells. (E) Temporal changes in the mean E-cad intensity profile between 48 and 92 hr for aggregates (Ecad-GFP/Oct4-mCherry) exposed to Chi (n = 7 aggregates, N = 3 replicates) and the control (n = 7 aggregates, N = 1 replicate). (F) The plot illustrates the polarization of E-cad (n = 14 aggregates, N = 3 replicates) with respect to the deformation of the aggregates between 72 and 92 hr; the thick and the dashed lines represent the mean and the mean ± SD, respectively. (G) T-Bra polarization (n = 11 aggregates) with respect to the aggregate deformation between 72 and 96 hr; the thick and the dashed lines represent the mean and the mean ± SD, respectively.

Aggregates exposed to Chi lose their spherical morphology and acquire a teardrop shape (Figure 1B, day 4, Video 1). We find that 30/37 or ~80% aggregates qualify as elongated with an elongation threshold set to 0.125 (see also Video 2). In contrast, 15/20 or 75% of control aggregates remained spherical (Figure 1b, day 4). At the pointed end of the Chi exposed aggregates, we observed an E-cadherin (E-cad)-rich region, which was absent in the control aggregates (Figure 1C, Figure 1—figure supplement 1). The E-cad pole emerges from an initially homogeneous distribution of E-cad (Figure 1D, Video 3). Likewise, a T-Brachyury (T-Bra)-rich pole, clearly visible at the tip of the aggregate at day 4, emerges from a spatially homogeneous distribution at day 3.

Video 1
Gastruloid polarization between 72 hr and 96 hr imaged with bright-field microscopy.
Video 2
Gastruloids polarization in a 96 wells plate between 72 hr and 100 hr after formation (mosaic aggregates made of 100 cells E14 +20 cells T-Bra-GFP) imaged by epifluorescence.

In magenta, aggregates were pulsed with Chi between 48 hr and 72 hr and have a T-Bra expression and polarization. In blue, control Gastruloids that were not pulsed and do not exhibit T-Bra expression.

Video 3
E-cadherin-GFP signal evolution during Gastruloid polarization between 72 hr and 96 hr imaged by epifluorescence.

Time-lapse imaging shows distinct time evolution of global E-cad and T-Bra signals. While E-cad is expressed from the early time points (Figure 1D, day 2), T-Bra expression follows exposure to Chi (Figure 1D and Video 4). The Chi pulse triggers a decay in E-cad level (mean intensity, Figure 1E and Video 5). T-Bra level, maximal just before removal of Chi, gradually decreases thereafter (Videos 2 and 6).

Video 4
T-Bra-GFP signal apparition during the Chi pulse from 48 hr to 72 hr imaged by epifluorescence.
Video 5
E-cadherin-GFP progressive decay during the Chi pulse from 48 hr to 72 hr imaged by epifluorescence.
Video 6
T-Bra-GFP signal evolution during Gastruloid polarization between 72 hr and 96 hr imaged by epifluorescence.

Most aggregates show a single pole of T-Bra (35/64), some display multiple poles (18/64) and 11/64 do not polarize (Video 2). We then asked whether the polarized expression of E-cad precedes, follows or is concomitant with the deformation of the aggregates. Using descriptors of aggregate’s shape and polarization of fluorescence signal (see Materials and methods), we found that E-cad and T-Bra polarize prior to the onset of tip formation (Figure 1F and G), suggesting a possible role of E-cad and T-Bra in the aggregate’s shape polarization.

E-cadherin expression defines an endoderm-like region in the gastruloid

To resolve the spatial distribution of E-cad and T-Bra expressing cells at the single-cell level, aggregates exposed to Chi were stained at day 4. As shown in Figure 2A, a group of E-cad expressing cells is localized at the tip, spatially segregated from, and surrounded by T-Bra expressing cells. Furthermore, we observed that this core expresses Sox17 (Figure 2A, inset, Figure 2—figure supplement 1) and Foxa2 (Figure 2—figure supplement 1, Video 7) – markers of the endoderm. We confirmed that Sox2 is present earlier but absent at 5 days-pp while Sox17 is retained (Figure 2—figure supplement 1). These observations lead us to conclude that the group of E-cad expressing cells demarcates an endoderm-like region in the gastruloids. Figure 2B shows a histogram of the various cell populations at the tip of aggregates. The core of E-cad/Sox17 expressing cells and the T-Bra expressing cells constitute the majority of the cell population near the tip (Figure 2B). Nevertheless, a minority outside the core expresses either Sox17 alone or in conjunction with T-Bra. To obtain some insight into the supracellular tissue organization, we further determined the local neighborhood of the different cell populations (Figure 2C). The E-cad/Sox17 expressing cells that form the core maintain a relatively larger simply-connected-component (126 of 131 Ecad+/Sox17+ cells) and a homotypic neighborhood (111 E-cad+/Sox17+ cells maintain an Ecad+/Sox17+majority neighborhood), which implies that they form a tightly packed group of cells. In contrast, the T-Bra expressing cells form multiple simply connected-components (20 components) suggesting that they are sparsely distributed around the core. The E-cad+/Sox17+ cells thus form a compact region that is flanked by sparse T-Bra+ cells and few other cell types that span widely about the tip (Figure 2D and Figure 2—figure supplement 2 for two other aggregates).

Figure 2 with 2 supplements see all
An endoderm-like tissue at the tip of the gastruloid.

(A) aggregate stained at 96 hrs-pp for E-cad and T-Bra; the inset shows the endoderm-like cells at the tip expressing both E-cad and Sox17, surrounded by T-Bra+ cells. (B) the bar chart delineates the population fraction of the different cell populations present near the tip (n = 3 aggregates: 268, 179, and 150 cells, N = 2 replicates) with the error bars indicating the SD. (C) Spatial connectivity graph (Delaunay Mesh) of the different cell populations in an aggregate fixed at 96 hr-pp (D) Spatial distribution of the different cell types near the tip of a representative aggregate (stained at 96 hr-pp), its projection and the respective population fractions as a function of the distance from the tip of the aggregate.

Video 7
Z-stack (one slice every 10 microns) of a 96 hr Gastruloid (made of 150 T-Bra-GFP cells) immunostained with FoxA2 and E-cadherin.

Endoderm is established from an epiblast-like population

To probe how the endoderm-like region is established in gastruloids, we performed time-lapse imaging of the aggregates at single cell resolution. At the early stages E-cad expression pervades the entire aggregate; It is present at every cell-cell contact forming a quite homogeneous network of junctions. However, this network undergoes a gradual fragmentation (Figure 3A and Videos 811). The level of E-cad decreases temporally while a small fraction is retained, which eventually localizes near the aggregate’s tip. Within our immunostainings, we found consistently the presence of some E-cad/T-Bra cells that express lower levels of E-cad compared to their neighbors devoid of T-Bra (Figure 3—figure supplement 1A, 92 hrs-pp). In view of earlier studies (Turner et al., 2014; Fernando et al., 2010), a gradual repression of E-cad via increasing levels of T-Bra may possibly account for the fall of the E-cad level in the junctional network. Furthermore, in immunostainings at 3 days-pp, we notice only a small fraction of cells – distributed in a salt and pepper manner – that express Foxa2 (Figure 3—figure supplement 1B). Therefore, at 72 hr-pp, we do not find an organized group of cells that can potentially yield the endoderm. Additionally, at this stage, the cell population in the aggregates can be broadly classified into three categories: a class of cells that express both E-cad and T-Bra and two classes that express either one of the two markers (Figure 3B, left). Additionally, the E-cad+/T-Bra- cells are also found to be the ones expressing Sox2, akin to an epiblast. The E-cad/T-Bra expressing cells constitute most of the cell population (~70% of the total) and are surrounded by the T-Bra expressing cells (Figure 3B, right). The cells expressing only E-cad – present in the minority – are present mainly within the core of the E-cad/T-Bra expressing cells (Figure 3B, right, inset). A spatial connectivity graph shows that the cells in the core (E-cad+/T-Bra+) are found to be tightly packed – with 70 out of 81 of E-cad+/T-Bra+ cells forming the largest connected component - and maintain a homotypic neighborhood (72 E-cad+/T-Bra+ cells maintain an E-cad+/T-Bra+ neighborhood) (Figure 3b, right). Yet again the cells expressing only T-Bra are sparsely wrapped around the core (13 components for 31 T-Bra+ cells) and therefore, have a relatively heterotypic neighborhood (12 T-Bra+ cells have an E-cad+/T-Bra+ majority neighborhood). Spatial distribution of the cell types (mean of n = 7 aggregates) at 72 hrs-pp depicts that the cells expressing only E-cad are mostly present within the E-cad+/T-Bra+ cell islands, whereas the T-Bra+ cells are situated at the periphery of the aggregate (Figure 3C). Interestingly, at later time-points but before the aggregates are fully polarized, we observed an ‘archipelago’ of E-cad expressing cells separated by T-Bra expressing cells (Figure 3D, 92 hrs-pp, Figure 3—figure supplement 1A). At day 4, the E-cad expressing cells exhibit low levels of N-cadherin and Snail1, supporting the absence of an EMT transition for the E-cad expressing cells (Figure 3—figure supplements 1C and 2). These data are consistent with recent observations in the mouse (Scheibner et al., 2021). Additionally, the islands of E-cad expressing cells were found to be positive for the pluripotency markers Oct4 (Figure 3D). The Oct4 expression correlates inversely with the T-Bra expression, suggesting pluripotency and an epiblast-like nature of these cells (Figure 3E). Altogether our data suggests that the endoderm-like region - identified at the end of day 4 – originates from islands of pluripotent and epithelial cells expressing E-cadherin.

Figure 3 with 2 supplements see all
The endoderm-like region originates from islands of pluripotent and epithelial cells expressing E-cadherin.

(A) Time lapse images showing a gradual fragmentation and loss of E-cad network at 73, 80, 85, and 92 hrs-pp; scale bar represents 100 µm (B) (left) The three different cell populations in the aggregate are marked at 72 hrs-pp: namely cells that express only T-Bra, cells that express both T-Bra and E-cad, and cells that express only E-cad. (right) the fraction of the total population of cells for the three classes are provided in the histogram (n = 7 aggregates: 126, 116, 121, 102, 85, 184, and 163 cells, N = 2 replicates) with the SD shown by the error bars; inset shows the spatial distribution of the cells in one such aggregate (right) Spatial connectivity graph is generated for the aggregate at 72 hrs-pp. (C) Spatial distribution of the population fraction of the different cell types as a function of the radial distance from the aggregate centre (n = 7 aggregates: 126, 116, 121, 102, 85, 184, and 163 cells, N = 2 replicates). (D) Islands of E-cad/Oct4 expressing cells surrounded by T-Bra+ cells are present within the aggregate fixed at 92 hr-pp; the inset zooms on a few such islands. (E) Pixel intensity correlation plot between Oct4 and T-Bra (n = 6 aggregates, N = 2 replicates).

Video 8
Two-photon time-lapse movie of Gastruloid polarization and elongation with E-cadherin-GFP and sulforhodamine B (SRB) tagging.
Video 9
Two-photon time-lapse movie of Gastruloid polarization and elongation with E-cadherin-GFP and sulforhodamine B (SRB) tagging.
Video 10
Two-photon time-lapse movie of Gastruloid polarization and elongation with E-cadherin-GFP and sulforhodamine B (SRB) tagging.

Four planes 12.5 µm apart are superimposed on the right panel.

Video 11
Two-photon rapid time-lapse movie of a Gastruloid at early phase of symmetry breaking (E-cadherin-GFP).
Video 12
Two-photon time-lapse movie of Gastruloid polarization and elongation with T-Bra-GFP and sulforhodamine B (SRB) tagging.

Tissue flows and a local sorting segregate islands of E-cadherin expressing cells

Our observations raise the possibility that the islands of E-cad+ cells sort and form a compact group of cells. To test this possibility, we analyzed cell movements prior to the establishment of the aggregate tip. We imaged the aggregates with inverted two-photon microscopy adding Sulforhodamine B (SRB) to the medium which enables to visualize cell contours and extracellular space. We perform optical flow (See Materials and method) on the SRB signal (Figure 4A–B, Videos 814) and reconstruct the coarse-grained velocity field within the tissue. The flow field clearly shows that there is a directed flow of cells towards the future region that will form the tip of the gastruloid (Figure 4A–B, Figure 4—figure supplement 1, and Videos 1517). E-cad- cells flow backward at the periphery, away from the tip, which creates a physical separation between the two populations: E-cad+ and E-cad- cells (Videos 810). Islands of E-cad+ cells are highly dynamic during their movement toward the tip (Video 11). The directed flow and recirculation are not observed in absence of Chi pulse (Figure 4—figure supplement 1).

Figure 4 with 2 supplements see all
Tissue flows and a local sorting segregate islands of E-cadherin expressing cells.

(A–B) Cellular movements are quantified during the aggregate elongation using two-photon imaging of the aggregates with Sulforhodamine B (SRB) added in the medium, which enables to visualize cell contours. Optic flow measurements are performed on the SRB signal and the obtained velocity fields overlapped on the GFP signal corresponding to (A) E-cad and (B) T-Bra (N = 3 replicates). (C) Box-whisker plot shows the distribution of the ratio of the cell-junction tension heterogeneity between E-cad expressing cells (+), and between E-cad expressing cells and their neighbors (-) at 72 hr-pp (n = 28 junctions, N = 2 replicates) and 96 hr-pp (n = 54 junctions, N = 2 replicates); 25th and 75th quartiles together with the minimum and maximum values are shown; the insets to the left depict regions on the E-cad+ cell islands where the angle measurements were made. No significant statistical difference between the two time points (Kolmogorov-Smirnov Test; p-value = 0.37) (D) Cartoon depicting the different steps leading to the formation of an endoderm-like region within the gastruloid. Upon addition of Chi, majority of the E-cad expressing cells begin to express T-Bra. The transient expression of T-Bra represses E-cad expression in T-Bra+/E-cad+. Formation of islands of E-cad expressing cells surrounded by T-Bra+ cells; these islands are transported to one end of the aggregate via a tissue-scale movement. Islands of E-cad expressing cells segregate to give rise to the endoderm.

Video 13
Two-photon time-lapse movie of Gastruloid polarization and elongation with E-cadherin GFP and sulforhodamine B (SRB) tagging.
Video 14
Two-photon time-lapse movie of Gastruloid polarization and elongation with T-Bra::GFP and sulforhodamine B (SRB) tagging.
Video 15
Velocity field obtained by optical flow on the sulforhodamine B signal of the movie 12 superimposed on the T-Bra signal.
Video 16
Velocity field obtained by optical flow on the sulforhodamine B signal of the movie 8 superimposed on the E-cadherin signal.
Video 17
Velocity field obtained by optical flow on the sulforhodamine B signal of the movie 12 superimposed on the sulforhodamine B signal.

Despite dynamic cell rearrangements and shear in the bulk of the aggregate, the islands of E-cad expressing cells are not fully fragmented, implying that physical forces maintain their cohesion (Video 11). The E-cad expressing cells in islands have a significantly smaller contact angle with the surrounding cells than with each other (Figure 4c, inset). Assuming that the cell-cell contacts are determined by interfacial tension (Supplementary material), we measured the angle of contacts between E-cad expressing cells within the islands and with neighboring cells (Figure 4C). They correspond to a significant higher tension at the outer boundary of islands at days 3 and 4 (Figure 4C, Figure 4—figure supplement 2). Such difference could account for the maintenance of E-cad+ cell islands during their transport as well as their segregation at the tip, where E-cad+ cells would sort from the T-Bra+ cells to form a large endoderm domain.

Discussion

In contrast to classical gastruloids, when aggregates of ESCs are grown in Activin and FGF, they go through a clear phase similar to the postimplantation epiblast. In this state, suppression of Wnt signaling leads to anterior neural development (Girgin et al., 2021) but, as we show here, exposure to Wnt signaling leads to fates associated with primitive streak, as evidenced by expression of T-Bra and the emergence of an endoderm-like region. We also observe directional and coordinated movements of cell ensembles that mimic some aspects of mammalian gastrulation, in particular the epithelial organization of the gastruloid at the time of Chi application. Under Chi exposure, that mimics the Wnt/β-catenin signaling, the pluripotent epiblast-like cells (with the exception of a few cells) experience a massive wave of T-Bra expression and a loss of E-cad-mediated contacts (Figure 4D). The cells near the periphery specifically exhibit high levels of T-Bra and low levels of E-cad expression (Figure 3B and C). A similar observation has been made on 2D micropatterns in which a T-Bra wave emanates and travels inwards, from the boundary where E-cad is absent (Martyn et al., 2019). Loss of E-cad contacts in parts of the aggregate leads to the appearance of pluripotent E-cad+ cell islands (Sox2 or Oct4 positive), that are enveloped by T-Bra expressing cells (Figure 3, B, D, Figure 3—figure supplement 1, and Figure 4D). All the while a coordinated motion of the cells within the aggregate arrange the islands of the E-cad/Sox2/Oct4 expressing cells at one pole of the aggregate. This pole protrudes outwards to form the tip. The E-cad islands subsequently segregate at the tip and are found to express markers characteristic of the endoderm (Figures 2 and 4D).

While we cannot rule out the possibility that the mechanogenetic trajectory followed by cells in the gastruloids may be different from that in the embryo, our data are consistent with recent observations in the embryo (Scheibner et al., 2021) that challenged the prevailing view that endoderm forms from a mesendodermal primodium. In the mouse (Scheibner et al., 2021) and in the gastruloids (our work and Vianello and Lutolf, 2020) the endodermal progenitors do not undergo an Epithelial-Mesenchymal transition (EMT) and emerge from a different pool of cells (E-cad+ /T-Bra-) than the mesodermal-like precursor cells (T-Bra+). Vianello and Lutolf further reported that within 7 days the endoderm primordium in the gastruloids give rise to different expression territories corresponding to anterior foregut, midgut and hindgut (Vianello and Lutolf, 2020), suggesting that what we observe in vitro follows closely the events in vivo. Altogether the in vivo and in vitro data point to a mechanism where the endoderm tissues originate from the epiblast via a trajectory that differs from that of the mesodermal cells.

A surprising feature of endoderm specification in gastruloids (see also Pour et al., 2019; Vianello and Lutolf, 2020) is the appearance of endodermal cells as small islands that coalesce into a continuous tissue. The evidence that a similar mechanism is at play in the mouse embryo remains partial, although a recent report suggests that endodermal progenitors emerge in small islands (see Figure 3 in Probst et al., 2021). In zebrafish, a similar mode of endoderm specification has been reported, where it is the predominant mode (Montero et al., 2005; Nair and Schilling, 2008; Warga and Nüsslein-Volhard, 1999). The clear manifestation of this mode of specification in the gastruloids might reflect that ancestral modes are emphasized in this model (Steventon et al., 2021).

The segregation of endodermal-like cells in the gastruloids is a consequence of a wave of cell state transitions, a global flow and surface tension heterogeneity. Whether the same mechanism exists at the primitive streak in the mouse embryo remains to be explored. The mechanism described here cannot be reduced to a simple cell-sorting mechanism based on differential adhesion. Different cellular mechanisms are at stake: advection by tissue flow, cell sorting by cellular motions, but also cell division, cell death, and cell differentiation that constantly modify the number of constituent cells and their pattern. How these different cell events lead to the eventual tissue pattern will require further study. Our work emphasizes the coupling between biochemical signaling and tissue flows during endoderm formation, and perhaps more generally during the morphogenesis of germ layers. Furthermore, it illustrates the potential of in vitro models of early embryogenesis to decouple and study these events.

Materials and methods

Cell culture and gastruloids

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A complete description of the culture conditions and the protocol for making gastruloids is present in Baillie-Johnson et al., 2015. Nevertheless, a twofold modification was made to the original protocol.

  1. Unless explicitly mentioned approximately 50–60 cells were seeded per well to generate smaller gastruloids.

  2. The gastruloids were exposed to a 12.5 ng/ml of bFGF (RD system ref: SUN11602) and 25 ng/ml of Activin A (RD system ref: 338-AC-050) throughout its development

* We formed our aggregates in low-adherence condition in 96 well plates (Costar ref: 7007) and microwell plates (400 um wells, SUNBIOSCIENCE ref: Gri3D).

List of cell lines used:

  1. the new E-cad-GFP/Oct4-mCherry cell line is described in Figure 1—figure supplement 1.

  2. T-Bra-GFP/NE-mKate2: the TBra-GFP/NE-mKate2 was generated in Sally Lowell group through a random integration of a NE-mKate2 plasmid (Blin et al., 2019) in a TBra-GFP cell line developed in Val Wilson group (Karagianni, 2017).The cell line was authenticated by Southern blot.

  3. E14Tg2a.4 mouse Embryonic Stem Cells (mESC) (MMRRC, University of California Davis, US).

All cell lines were tested free from mycoplasma contamination by qPCR.

Immunostaining

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Immunostaining was performed by fixing the aggregates (4% PFA in PBS with 1 mM CaCl2 and 0.49 mM MgCl2 overnight at 4 °C), followed by washing and blocking for 1 hour in PBSFT buffer (PBS with 10% FBS, 0.2% Triton X-100). Aggregates were incubated with primary antibodies, washed, and incubated again with secondary antibodies. The incubations were done overnight at 4 °C.

Mentioned below is a list of primary antibodies used in this study:

AntibodiesSpeciesReferenceProviderDilution
BrachyuryGoatAF2085RD system1:80
E-cadherinRatM108Takara1:200
anti-GFPChickenGFP-1020Aves1:1000
Sox17GoatAF1924RD system1:80
FoxA2Goatsc-6554Santa-Cruz1:50
CDX2RabbitMA514494Thermo1:200
Gata6GoatAF1700RD system1:100
Sox2MouseSc-365823Santa Cruz1:100
SnailGoatAF3639RD system1:50

*We used Alexa dyes (ThermoFisher) against the primary antibodies.

Live and fixed imaging

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Epifluorescence time-lapse imaging of gastruloids was achieved in a chamber – maintained at 37 °C, 5% CO2 with a humidifier – using an AxioObserver inverted microscope (Carl Zeiss) with a 20 x LD Plan-Neofluar 0.4 NA Ph2 objective. A white LED source (Laser2000, Kettering UK) was used for illumination. A second setup with similar specifications was also utilized for long-term imaging.

Fixed gastruloids were loaded on MatTek dishes (MatTek corporation, ref: P35G-1.5–14 C) and imaged using a confocal microscope (Zeiss LSM 880) with a 40 × 1.2 NA W Korr objective.

Biphoton imaging of gastruloids was achieved in a chamber- maintained at 37 °C, 5% CO2 with a humidifier – using a Zeiss 510 NLO (Inverse - LSM) with a femtosecond laser (Laser Mai Tai DeepSee HP) (900 nm) with a 40 x/1.2 C Apochromat objective. Seventy-two hr old gastruloids were transferred from 96-well plates to either MatTek dishes (MatTek corporation, ref: P35G-1.5–14 C) or to microwell plates (400 um wells, SUNBIOSCIENCE ref: Gri3D). To visualize intercellular space, we added 32 µL/mL of a Sulforhodamin B solution (1 mg of Sulforhodamin B powder, 230,162 Aldrich per mL of medium) to the medium. We imaged sub-volumes of gastruloids (10 slices z-stacks with a z-interval of 2 µm) near their midplane during a total time between 10 h and 24 h (time interval between two frames between 2 and 4 min depending on the experiment). We imaged the GFP (T-Bra-GFP/NE-mKate2 and E-cadherin-GFP/Oct4-mCherry cell lines) and the Sulforhodamin B channels using a non-descanned detector.

Cryosection

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Aggregates were embedded in Optimal Cutting Temperature (OCT) after fixing in 4% Paraformaldehyde (PFA) and then flash frozen in liquid nitrogen. Slices of 25 and 30 µm were manually cut from the resin with a cryostat (Leica CM3050 S). The slices were mounted on Superfrost Plus slides before proceeding with immunostaining.

Relative surface tension

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Under the assumption that the final shape and configuration of the cells are largely dominated by surface tension, we can compute the relative tension between the E-cadherin/non-E-cadherin (γ+-) and the E-cadherin/E-cadherin expressing cells (γ++) as the reciprocal of the sum of the cosines of the two angles subtended at the interface of the E-cadherin/non-E-cadherin cells (Figure 4C).

γ+-γ++=1cos θ1 +cos θ2

Image processing and data analysis triangulation/probability map

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The gastruloids were initially manually segmented using brightfield images or a combination of brightfield and the fluorescence signal. An artificial convolutional neural network, UNET (Ronneberger et al., 2015) was also employed to yield a high-throughput pipeline for generating binary masks of aggregates with brightfield images. The UNET was trained on an augmented dataset (n = 390 and n = 264 images for aggregates generated from Ecad/Oct4 line and T-Bra/NE-mKate2 lines respectively) and then applied onto the time series aggregate images to obtain binarized masks. Any imperfections in the generated masks were manually corrected in FIJI/ImageJ. The mean signal intensity of the aggregates was computed by averaging the pixel intensities within the binary masks.

The overall elongation of the aggregates at each time point was quantified by determining the ratio of the eigenvalue pairs of the inertia tensor of the binary mask. This is equivalent to finding the ratio of the major to the minor axes of the best-fit ellipse to the mask. Furthermore, to precisely capture the onset of the tip formation we relied on Fourier-Elliptic Descriptors3(FED) as a shape descriptor (Kuhl and Giardina, 1982). The aggregate perimeter was defined by a set of n-harmonics/ellipses (n = 1,2,3 …) – each associated with four coefficients – such that the difference of area between the aggregate mask and the morphology obtained from the harmonics was less than 2%. The onset of tip formation was determined using the 2nd FED harmonic at each time point. The corresponding coefficients were transformed to the lengths of the major and minor axes of the ellipse. The magnitude of the second harmonic was then taken to be the product of the lengths of the two axes, which is a proxy for the extent of tip formation and shape polarization.

The polarization of the fluorescence was defined as the maximum of contrast between the two-halves of the aggregate. It was calculated in two-steps: first the aggregate mask was chopped into two halves about the eigenvector of the inertia matrix, which passes through the centroid of the mask. The contrast was then calculated as (I_max-I_min)/(I_max + I_min) where I_max and I_min represent the intensities of the brighter and less bright halves, respectively. The contrast maximum was then determined by angular scanning by repeatedly rotating the cutting plane by 5°.

The different cell-types in the confocal image-stacks were manually identified and tagged via Cell Counter – a built-in FIJI plugin. Corrections were made to ensure that each cell was designated a unique identity. The positions of the marked cells were extracted for further processing. The centroids of the cell were extracted to create a neighborhood graph and deduce spatial statistics. The cell populations at the aggregate tip (at 96 hr-pp) are spatially binned to generate probability maps of the different cell types along the tip. Owing to the sphericity of the aggregates at 72 hrs-pp, cell positions are normalized to lie in a unit sphere. Aggregates are registered via their common origin and all the cell populations are pooled to create a spatial probability density map (using SmoothKernelDistribution function in Mathematica). A numerical integration of the density function yields the probability of finding the various cell types as a function of the distance from the origin.

To build the graph we generated a Delaunay triangulation (using the built-in DelaunayMesh in Mathematica) from the cell centroids and pruned any edges that were more than 12 um in length (avg. size of a cell). The neighborhood type of a cell is assigned by counting the cell types of all the adjoining cells and taking the most dominant cell-type as the neighborhood type; for instance, if majority of the neighboring cells, around an E-cad+/T-Bra+ cell, are also E-cad+/T-Bra+ then the cell has a homotypic neighborhood, else the neighborhood is designated as being heterotypic.

To measure velocity fields corresponding to Gastruloids polarization and elongation, we use the signal obtained from the Sulforhodamin B (SRB) channel in two-photon timelapses (which is present in all the parts of the Gastruloid in contrary to signals such as T-Bra GFP or E-Cadherin GFP). The SRB signal corresponds to (i) cell contours, (2) dead cells, and (3) bright spots of subcellular size moving rapidly corresponding probably to vesicles are visible. As dead cells and bright spots are much brighter than cell contours, we filter them with a thresholding operation, and perform the optic flow on the filtered image where only cell contours are visible after timelapse registration to remove rapid rotations and translations of the aggregate. We use a custom-made Matlab optic flow code based on the Kanade Lucas Tomasi (KLT) algorithm with a level 2 pyramid and a window size corresponding to a square of 2 cells by 2 cells (Lucas and Kanade, 1981).

Images in the timeseries data were registered using MultiStackReg – an ImageJ plugin – and custom Matlab scripts. The scripts for analyzing data, image processing, neural networks and computer vision techniques were implemented in Wolfram Mathematica 12 and Matlab. Analysis scripts are provided in the supplemental information of this paper.

Data availability

All data generated or analysed during this study are included in the manuscript and supporting files. The source data and the scripts at https://zenodo.org/record/5727050.

The following data sets were generated
    1. Hashmi A
    2. Tlili S
    3. Perrin P
    4. Martinez-Arias A
    (2020) Zenodo
    Cell-state transitions and collective cell movement generate an endoderm-like region in gastruloids.
    https://doi.org/10.5281/zenodo/5727050

References

  1. Book
    1. Karagianni EP
    (2017)
    Dissecting lineage specification in episc and neuromesodermal progenitor cultures doctoral dissertation
    The University of Edinburgh.
  2. Conference
    1. Lucas BD
    2. Kanade T
    (1981)
    An iterative image registration technique with an application to stereo vision
    Proceedings of the 7th International Joint Conference on Artificial Intelligence Volume 2, IJCAI’81. pp. 674–679.
  3. Book
    1. Wolpert L
    2. Smith J
    3. Jessell T
    4. Lawrence P
    5. Robertson E
    6. Meyerowitz E.
    (2006)
    Principles of Development (3rd ed)
    USA: Oxford University Press.

Decision letter

  1. Isabelle Migeotte
    Reviewing Editor; Université Libre de Bruxelles, Belgium
  2. Didier YR Stainier
    Senior Editor; Max Planck Institute for Heart and Lung Research, Germany
  3. Isabelle Migeotte
    Reviewer; Université Libre de Bruxelles, Belgium

In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.

Decision letter after peer review:

Thank you for sending your article entitled "Cell-state transitions and collective cell movement generate an endoderm-like region in gastruloids" for peer review at eLife. Your article is being evaluated by 3 peer reviewers, including Isabelle Migeotte as the Reviewing Editor and Reviewer #1, and the evaluation is being overseen by Didier Stainier as the Senior Editor.

The reviewers agree that the manuscript reports an interesting and original observation in gastruloids. However, there is currently no evidence to propose that such mechanism would be present in embryos. Additionally, there is consensus that the methods are not sufficiently explained, the reproducibility is not clearly quantified, and some claims would require a larger number of aggregates/cells to be solid.

Reviewer #1:

General assessment

The manuscript by Hashmi et al., describes the emergence of endoderm-like cells in a stem cells based embryo model. The particularity of the protocol is that it stimulates transition through an epiblast-like state, then differentiation towards mesoderm after a pulse of Chiron, a Wnt agonist. In those conditions, islets of E-cadherin positive cells emerge, surrounded by Ecad+Brachyury+, then Brachyury positive cells. Those islets fuse together at the tip, possibly due to distinct surface tension and directed cell movements, and express endoderm markers such as Sox17 and FoxA2.

It is an original approach and concept, raising new questions and possibilities about the mechanisms of endoderm emergence in the mouse embryo. The manuscript is well written and clear.

Concerns

1.The data would benefit from increased clarity in stating, for each experiment, the proportion of aggregates in which a given phenomenon was observed, as well as the number of cells counted in each aggregate, in particular in supplementary figures.

2. For the migration analysis, it could be interesting to distinguish each cell trajectory in order to distinguish behaviours of the subpopulations.

3. In terms of the surface tension analysis, performing a similar analysis at different timepoints might be helpful to understand how the islets come to fuse at the tip.

4. I am not sure about the specificity of the gata6 staining, not that it adds a lot to the story.

5. The authors might want to discuss how those aggregates evolve, and whether the endoderm-like cells have a potential for further differentiation.

Conclusion

Overall it is an interesting and original observation, well substantiated. More details on the quantification methods would help convince about the solidity of the model: chance of obtaining those cells, amount of cells of each subpopulation including those described in supplementary figures, technical possibility of sorting them for transcriptome analysis etc. In terms of format, I think this report would better fit as a short report than full research article.

Reviewer #2:

In this manuscript, the authors proposed a new mechanism of endoderm formation in 3D gastruloid models based on cell migration and fragmentation. Specifically, they found that E-cad is first uniformly expressed inside mESC aggregates. After exposure to Wnt agonist Chiron (Chi), a gradual repression of E-cad and an increase of T-Bra were detected. Cells in the core are tightly packed and express E-cad. T-Bra expressing cells are sparsely wrapped around the core. A directed flow of E-cad expressing cell islands surrounded by T-Bra expressing cells help to accumulate E-cad expressing cells to the tip of the aggregate and form endoderm domain.

I think the dynamical expression of E-cad and T-Bra and the directed cell flow reported in this manuscript are interesting. The results and videos have showed that the elongation and formation of endoderm region is a collective cell behavior rather than single cells undergo epithelial-to-mensenchymal transition. But I am not convinced that the process is done based on the three-step mechanism proposed by the authors. Moreover, I am not sure if this phenomenon really happened in mouse embryo development, giving the considerable differences between gastruloid model and embryo. Since there are methods culturing mouse embryo in vitro up to the early organogenesis stage, I would suggest the authors to provide more evidence showing that the proposed mechanisms might also happen in vivo.

In addition, the manuscript provides too little information to understand the phenomenon. And they did not clearly introduce experimental and computational methods they used to acquire the results. I listed some of my comments below.

1. Did all 3D aggregates become elongated shape in the presence of Chi? If not, what do E-cad and T-Bra expressions and cell migration dynamics look like in those spherical aggregates? Without Chi, inside the spherical aggregates, do they also have cell migration since the aggregates keep growing larger?

2. When did the collective cell migration start? Right after exposing to Chi? Or after some percentage of cells become T-Bra positive cells? Did the gastruloid keep elongating with directed cell flow inside it when cultured for a long time?

3. Are the collective cell migration driven by the T-Bra cells? Is it a spontaneous property of E-cad cells when the E-cad cell density exceed some critical threshold (e.g. glassy dynamics)?

4. Does the elongation and migration dynamics depend on the concentration of Chi, size of the aggregates? I noticed the authors used different initial seeding densities.

5. For the elongated cell aggregates, one side of cells express E-cad. How about the other side of cells? Did they all become mesoderm-like (T-Bra+) cells?

6. Many results are only based on several (3 or 4) gastruloids. For example, figure 1 (d) (e), figure 2 (b), figure 3(c). And in Figure 4 (b), the authors only quantify 13 junctions, probably in the same gastruloid. Due to the heterogeneity among the gastruloids, I am not sure how repeatable the experiments are. Can those observations really reflect phenomenon happened inside the majority of gastruloids? I think the authors should provide some quantifications of the percentage of observing the reported results among a large number of gastruloids.

Unclear results or experimental descriptions:

1. Can the authors show a schematic of the experimental process, such as the time of adding Chi and fixation?

2. 'We find that 30/37 … set to 0.125.' How did the authors define and calculate the elongation ratio and E-cadherin polarization ratio? How did the authors define the elongation threshold?

3. Figure 1 (a): what is the y axis? 1 (d): how did the author measure the E-cad and T-Bra expression? Fixing at different time points or live imaging? If it is live imaging, is the acquisition process influenced by adding and removing Chi? 1(e) how can the authors get continuous results for polarization?

4. Figure 2 (b) Are those dots represents the nuclear position? Can the authors provide the 3D view of the whole gastruloid? (c) What information the authors are trying to get from the connectivity graph?

5. Figure 3 (a) What are those white dots in the images, also in video 6? Can the authors replace t1, t2, t3, t4 with the real time, such as 24h, 36h? (d) How did the authors calculate the intensity? How did the authors normalize the intensity? The schematic in (b) is hard to understand. What do the light and dark colors represent? How did the authors measure theta_1 and theta_2, especially in 3D situation? More quantitative information should be acquired from (a).

6. I am not able to identify islands of E-cad expressing cells in Figure 3 (a) and video 6.

Reviewer #3:

In this manuscript Hashmi et al., describe the emergence of an endoderm population in a gastruloid model. They observe that endoderm cells are positive for E-Cad, likely express E-Cad continuously from an epiblast state, initially form small islands, and finally coalesce into a larger endoderm region at the pole of the gastruloid. There are several issues with this manuscript in its current form.

1. No evidence is provided that there is an relationship between how endoderm forms in this gastruloid model and in vivo. In fact, endoderm is believed to derive from a restricted area in the anterior primitive steak. This is evident from the mouse imaging data of Mcdole et al., Cell 2018 as well as from more recent genetic labeling experiments (Probst et al., bioRxiv 2020). It is well known that cells of different germ layers may self-segregate and this may drive the behavior observed here downstream of heterogenous differentiation in the gastruloids, but that is not necessarily the mechanism which occurs in vivo. The authors suggest that their experiments show something about endoderm formation in vivo without addressing this point which substantially diminishes from the interest of the manuscript.

2. The authors suggest that this view of endoderm differentiation, which doesn't require full EMT is novel, however, much of the observations here are already known. It is known that future endoderm cells do not down regulate E-Cadherin but instead must continue to express it. They also are known to migrate collectively rather than as single cells in a cadherin-dependent way (Montero et al., Development 2005; reviewed in Nowotschin et al., Development 2019). The authors should discuss this literature and make clear which aspects of the proposed mechanisms are novel.

3. The authors are assessing the status of EMT based on a single marker, E-Cad. If this is a major point of the manuscript other markers e.g. Snail, N-Cad should be examined.

4. It is well known that embryoid bodies form an outer layer of visceral endoderm e.g. Concouvanis and Martin Cell 1995, Doughton et al., PLOS One 2010. None of the markers here are exclusive to definitive endoderm (including Sox17 which is used throughout, see Artus et al., Dev Biol 2011). The authors should address the possibility that their observations may be consistent with a similar mechanism and may not reflect definitive endoderm differentiation.

[Editors’ note: further revisions were suggested prior to acceptance, as described below.]

Thank you for resubmitting your work entitled "Cell-state transitions and collective cell movement generate an endoderm-like region in gastruloids" for further consideration by eLife. Your revised article has been evaluated by Didier Stainier (Senior Editor) and a Reviewing Editor.

The manuscript has been improved but there are some remaining issues that need to be addressed, as outlined below:

Conceptual concern:

The notion that endoderm specification does not requite EMT is indeed backed up by data in the embryo, and this part is now adequately covered in the paper.

The observation that, in gastruloids, endoderm cells arise as islets that get sorted from the other cells possibly though differences in cell junctions tension is interesting and well substantiated. It is supported by studies in vitro in different species, including rather ancient experiments. However, the referees point that the evidence that a similar mechanism is at play in the mouse embryo is still weak, and would suggest tempering that claim (revise paragraph starting at line 233 in discussion).

Technical concern:

Although the reviewers acknowledge that the authors have increased the number of gastruloids and cells in most quantifications, they argue that the number is not huge yet in view of the variability. Therefore they propose that:

– number of samples and replicates should be added to the figure legends for clarity.

– statistical analysis should be reinforced through addition of a power calculation.

Format:

Reviewers point that the paper would be better suited as a short report. A change of format at this stage may present a risk of losing clarity. We would nonetheless recommend to condense the data notably through fusion of the supplementary figures in one (or maximum two) per main figure.

Please find below the comments of an additional reviewer consulted.

Reviewer #4:

Hashmi et al., present a gastruloid model for the emergence of endoderm-like cells after treatment with a Wnt agonist. These gastruloids appear to resemble the posterior region of the mouse embryo during gastrulation, segregating into T+ and Foxa2+ regions, the latter of which retains E-cadherin, paralleling recent studies which have suggested endoderm cells do not undergo EMT on exit from the epiblast. The data they present are intriguing, and suggest a conserved mechanism for sorting mesoderm and endoderm, however it is very difficult to draw direct comparisons to the mouse embryo. More information on the emergence, behaviour and ultimate fate of these endoderm-like cells would better substantiate their model as well as provide valuable new information, however this is technically challenging and would result in a much larger study than what is presented here. I agree with Reviewer 1 that the fit for this manuscript is more suited for a short report than a full research article.

In general, the authors have addressed each reviewer's points, provided new data as well as clarified their methods and increased the number of gastruloids used in each analysis. While the number of samples and replicates used are presented in a supplementary table, it would be helpful for the reader if these were included either in the figure legends or the figure themselves. The increase in sample number is not huge, however, (particularly given the variability between gastruloids) and the study could benefit from some power calculations. While there are clearly more avenues for the authors to expand up on or follow up, regarding the manuscript in its current state they have addressed the majority of the reviewer's questions and concerns.

https://doi.org/10.7554/eLife.59371.sa1

Author response

Reviewer #1:

General assessment

The manuscript by Hashmi et al., describes the emergence of endoderm-like cells in a stem cells based embryo model. The particularity of the protocol is that it stimulates transition through an epiblast-like state, then differentiation towards mesoderm after a pulse of Chiron, a Wnt agonist. In those conditions, islets of E-cadherin positive cells emerge, surrounded by Ecad+Brachyury+, then Brachyury positive cells. Those islets fuse together at the tip, possibly due to distinct surface tension and directed cell movements, and express endoderm markers such as Sox17 and FoxA2.

It is an original approach and concept, raising new questions and possibilities about the mechanisms of endoderm emergence in the mouse embryo. The manuscript is well written and clear.

We thank the reviewer for the positive comments.

Concerns

1.The data would benefit from increased clarity in stating, for each experiment, the proportion of aggregates in which a given phenomenon was observed, as well as the number of cells counted in each aggregate, in particular in supplementary figures.

We have increased the number of experiments and are providing in a table (Table 1) for each figure the number of observations (number of gastruloids, number of independent experiments).

2. For the migration analysis, it could be interesting to distinguish each cell trajectory in order to distinguish behaviours of the subpopulations.

Distinguishing each cell trajectory in a 3D free-floating aggregate is a challenging task, and we have to improve imaging and computational approaches to do so, which is beyond the scope of this manuscript. However, to address this point, we have extended the optical flow analysis on 2-photon and epifluorescence videos. We see collective cell flows toward the posterior pole and cells that recirculate backwards at the periphery of the aggregate. Analysis of cell flows and E-cad expression show a clear correlation between the two (New Figure 4 A and Video 16). Cells that recirculate backwards are Bra+ E-cad- that loose Bra expression, while cells remaining at the pole are either Bra+ or Bra-/E-cad+ (Figure 4 A-B Videos 15-16).

3. In terms of the surface tension analysis, performing a similar analysis at different timepoints might be helpful to understand how the islets come to fuse at the tip.

We have made additional analysis from confocal/2-photon images at 72 and 96h, to capture the segregation of the islets. We measured contact angles, and thus inferred ratio of tensions for E-cad expressing islands. The surface tension at the border of E-cad islands remains high but constant. The data are shown in Figure 4C, Figure 4 —figure supplement 2. The Videos of E-cad (Videos 8-11) highlight that the cells are very dynamic, dividing and moving in 3D. The high surface tension is likely to prevent the islets to disrupt and remain compact while they segregate at the tip.

4. I am not sure about the specificity of the gata6 staining, not that it adds a lot to the story.

We decided to not include this data on this staining as it is not relevant to the main points of our story.

5. The authors might want to discuss how those aggregates evolve, and whether the endoderm-like cells have a potential for further differentiation.

We show that cells express Sox17 at 120 hrs-pp (Figure 2 —figure supplement 2). A recent manuscript from Lutolf lab (Vianello and Lutolf, biorXiv 2021) reports that different endodermal types arise within 7 days of culture, including expression territories corresponding to anterior foregut, midgut and hindgut. Our study focuses on the symmetry breaking events leading to the early endoderm formation, prior to this specification. Vianello and Lutolf was not submitted at the time of the 1st submission of our paper; we now refer to it and to its findings in the discussion.

Conclusion

Overall it is an interesting and original observation, well substantiated. More details on the quantification methods would help convince about the solidity of the model: chance of obtaining those cells, amount of cells of each subpopulation including those described in supplementary figures, technical possibility of sorting them for transcriptome analysis etc. In terms of format, I think this report would better fit as a short report than full research article.

We thank the reviewer again for recognizing the originality of our work and we hope that the new data provided address their points.

Reviewer #2:

In this manuscript, the authors proposed a new mechanism of endoderm formation in 3D gastruloid models based on cell migration and fragmentation. Specifically, they found that E-cad is first uniformly expressed inside mESC aggregates. After exposure to Wnt agonist Chiron (Chi), a gradual repression of E-cad and an increase of T-Bra were detected. Cells in the core are tightly packed and express E-cad. T-Bra expressing cells are sparsely wrapped around the core. A directed flow of E-cad expressing cell islands surrounded by T-Bra expressing cells help to accumulate E-cad expressing cells to the tip of the aggregate and form endoderm domain.

I think the dynamical expression of E-cad and T-Bra and the directed cell flow reported in this manuscript are interesting. The results and videos have showed that the elongation and formation of endoderm region is a collective cell behavior rather than single cells undergo epithelial-to-mensenchymal transition. But I am not convinced that the process is done based on the three-step mechanism proposed by the authors. Moreover, I am not sure if this phenomenon really happened in mouse embryo development, giving the considerable differences between gastruloid model and embryo. Since there are methods culturing mouse embryo in vitro up to the early organogenesis stage, I would suggest the authors to provide more evidence showing that the proposed mechanisms might also happen in vivo.

In addition, the manuscript provides too little information to understand the phenomenon. And they did not clearly introduce experimental and computational methods they used to acquire the results. I listed some of my comments below.

We are aware that our manuscript does not provide direct evidence that the mechanism that we show in gastruloids is present in the embryo. However, our data are not at odds with the existing literature, in particular two recently published works (Probst…and Arnold, Development 2020 and Schneiber et al., Nature Cell Bio 2021). The latter (which was not published at the time of our 1st submission) reports that endoderm progenitors cells do not undergo a mesenchymal transition in the primitive streak of the mouse embryo, which is consistent with our observations. As discussed in the general comments above, we now highlight the links between the scattered observations that exist in the literature. We also mention the possibility that the mechanogenetic trajectory followed by cells in the gastruloids may be different from that in the embryo. In our opinion, this does not diminish the interest of our manuscript as it reports a mechanistic description of the symmetry breaking event.

1. Did all 3D aggregates become elongated shape in the presence of Chi? If not, what do E-cad and T-Bra expressions and cell migration dynamics look like in those spherical aggregates? Without Chi, inside the spherical aggregates, do they also have cell migration since the aggregates keep growing larger?

We now provide more data of 3D aggregates in the presence and absence of Chi (Video 2). A large fraction of aggregates are already elongated in the presence of Chi at 96 hours (30/64). All the elongated aggregates at 96 hours show a single pole of T-Bra. Some aggregates are multipolar both in shape and T-Bra some (18/64). Some aggregates are not elongated at 96hrs (15/64). Such aggregates show a non-polarized pattern of E-cad (Figure 4 —figure supplement 2). In the absence of Chi, the aggregates grow isotropically as shown by the (isotropic) flow pattern (Figure 4 —figure supplement 1).

2. When did the collective cell migration start? Right after exposing to Chi? Or after some percentage of cells become T-Bra positive cells? Did the gastruloid keep elongating with directed cell flow inside it when cultured for a long time?

The collective cell movement happens after removal of Chi (See for example Video 15). The gastruloids keep elongating with direct cell flow inside it (Figure 4 A-B and Videos 12-14).

The aggregate forms a tip while the collective motion is observed. In our protocol using FGF and Activin, the aggregates do not elongate as much as in the standard protocol. However, we have not looked at aggregates beyond 120 hrs post-plating since the larger-sized aggregates require different experimental conditions (shaker in particular, making live imaging tricky).

3. Are the collective cell migration driven by the T-Bra cells? Is it a spontaneous property of E-cad cells when the E-cad cell density exceed some critical threshold (e.g. glassy dynamics)?

The correlation between maximal shear and the localization of the interface between T/Bra+ and not T/Bra- indicate the role of T/Bra cells in the collective movement (Figure 4B and Figure 4: Figure sup 1). The islands of E-cad expressing cells are within the T/Bra+ domain and thus move together with the T/Bra+ cells. We cannot currently quantify the recirculation at the interface between E-cad+/Bra- islands and E-cad-/Bra- cells as this would require a cell line to be able to track individual cells, at least a two-colour cell line such as an E-cad/histone labelled line.

4. Does the elongation and migration dynamics depend on the concentration of Chi, size of the aggregates? I noticed the authors used different initial seeding densities.

We used the Chi concentration that is commonly used in the “gastruloid” community and didn’t investigate the concentration dependence. How the elongation and collective cell movement depend on the initial size is an interesting question but is beyond the scope of our study. We are currently limited by the number of videos we can obtain with 2-photon microscopy and couldn’t perform a systematic study on the size. We used between 50 and 200 cells as initial conditions. For these different sizes, we didn’t notice qualitative differences in the flow observed by 2-photon imaging.

5. For the elongated cell aggregates, one side of cells express E-cad. How about the other side of cells? Did they all become mesoderm-like (T-Bra+) cells?

We have addressed this point by additional immunostainings. The other side is not T/Bra and shows N-cad expression (Figure 3 —figure supplement 3) and fibroblast phenotypes with cavities and possibly reach in ECM as suggested by imaging sulforhodamine B which marks extracellular space (Videos 12-14).

6. Many results are only based on several (3 or 4) gastruloids. For example, figure 1 (d) (e), figure 2 (b), figure 3(c). And in Figure 4 (b), the authors only quantify 13 junctions, probably in the same gastruloid. Due to the heterogeneity among the gastruloids, I am not sure how repeatable the experiments are. Can those observations really reflect phenomenon happened inside the majority of gastruloids? I think the authors should provide some quantifications of the percentage of observing the reported results among a large number of gastruloids.

We are now providing more data using epifluorescence, confocal, and biphoton imaging on live and stained gastruloids. The number of gastruloids/cells and replicates is provided in Table 1.

Unclear results or experimental descriptions:

1. Can the authors show a schematic of the experimental process, such as the time of adding Chi and fixation?

We added a small panel in the main Figure 1 to make this clear.

2. 'We find that 30/37 … set to 0.125.' How did the authors define and calculate the elongation ratio and E-cadherin polarization ratio? How did the authors define the elongation threshold?

The elongation is measured by fitting an ellipse to the aggregate contour and is computed as (1 – (minor-axis/major-axis)), also sometimes referred as ellipticity.

The elongation threshold was selected as 0.125 or the 75% quartile of the Chi – aggregates. E-cadherin polarization was computed as explained in the main text and the supplementary method: the signal polarization is defined as the maximum of contrast between the two-halves of the aggregate. It was calculated in two-steps: first the aggregate mask was chopped into two halves about the eigenvector of the inertia matrix, which passes through the centroid of the mask. The contrast was then calculated as (Imax-Imin)/(Imax+Imin) where Imax and Imin represent the intensities of the brighter and less bright halves, respectively. The contrast maximum was then determined by angular scanning by repeatedly rotating the cutting plane by 5°

3. Figure 1 (a): what is the y axis? 1 (d): how did the author measure the E-cad and T-Bra expression? Fixing at different time points or live imaging? If it is live imaging, is the acquisition process influenced by adding and removing Chi? 1(e) how can the authors get continuous results for polarization?

Elongation is measured as 1 – (ratio between the length of the minor axis and that of the major axis of the aggregates). It is measured from live imaging using epifluorescence. The polarization is measured from day 3 (Figure 1E) after Chi removal.

4. Figure 2 (b) Are those dots represents the nuclear position? Can the authors provide the 3D view of the whole gastruloid? (c) What information the authors are trying to get from the connectivity graph?

Owing to the constraints imposed by the number of markers to be stained, most stainings used for the analysis in Figure 2 B-D did not have nuclear staining. However, other nuclear markers such as Bra and membrane staining such as Ecad were utilized to determine the cell centroids. Automation could not be utilized at this step and identifying different cell populations needed manual intervention. The connectivity graph quantifies the closeness/sparseness of the different cell populations, and here it additionally tells whether a particular cell population has a homotypic or a heterotypic cell neighbourhood.

5. Figure 3 (a) What are those white dots in the images, also in video 6? Can the authors replace t1, t2, t3, t4 with the real time, such as 24h, 36h? (d) How did the authors calculate the intensity? How did the authors normalize the intensity? The schematic in (b) is hard to understand. What do the light and dark colors represent? How did the authors measure theta_1 and theta_2, especially in 3D situation? More quantitative information should be acquired from (a).

The white dots visible in Old Figure 3 A and now Videos 12-14 correspond to dead cells which are marked by sulforhodamine B (cross-talk from the red to the green channel).

We have replaced t1-t4 with the actual timings that were provided in the Figure caption. The normalization of the intensities is done by using the maximum intensities of the respective channels.

The authors think that the reviewer is referring here to figure 4b (now Figure 4C and Figure 4: figure supplement 2) for the angles. Angles can only be specified in a 2D context (between lines) even in a 3D configuration (surfaces). The angles were measured by drawing tangents to the contours at the vertex where E-cad/Ecad cells meet (and surrounded by a E-cad- cell). Both theta angles are subtended between the respective tangents and the imaginary line extending the E-cad/E-cad junction.

6. I am not able to identify islands of E-cad expressing cells in Figure 3 (a) and video 6.

Islands of E-cad expressing cells are visible in Figure 3D and Figure 3: figure supplement 1 (staining/confocal), but we agree that they are more difficult to identify from the live 2-photon data (old Figure 2A and old video 6). We clarify this point by providing high resolution 2-photon videos (Video 8 with circled islands and Videos 9 and 10).

Reviewer #3:

In this manuscript Hashmi et al., describe the emergence of an endoderm population in a gastruloid model. They observe that endoderm cells are positive for E-Cad, likely express E-Cad continuously from an epiblast state, initially form small islands, and finally coalesce into a larger endoderm region at the pole of the gastruloid. There are several issues with this manuscript in its current form.

1. No evidence is provided that there is an relationship between how endoderm forms in this gastruloid model and in vivo. In fact, endoderm is believed to derive from a restricted area in the anterior primitive steak. This is evident from the mouse imaging data of Mcdole et al., Cell 2018 as well as from more recent genetic labeling experiments (Probst et al., bioRxiv 2020). It is well known that cells of different germ layers may self-segregate and this may drive the behavior observed here downstream of heterogenous differentiation in the gastruloids, but that is not necessarily the mechanism which occurs in vivo. The authors suggest that their experiments show something about endoderm formation in vivo without addressing this point which substantially diminishes from the interest of the manuscript.

This is an important point and we refer to it in our opening statement. A gastruloid is not an embryo but a model for certain events that happen in the embryo. In this case our study highlights some aspects of gastrulation that may have been overlooked and makes a well-grounded proposal for the origin of the endoderm. Importantly, since our first submission, a report from Lickert and colleagues (Schneiber et al., Nat Cell Bio 2021) has shown that endoderm formation in the mouse doesn’t require mesenchymal transition, which strongly substantiates our findings and the relevance of our observations in vitro.

2. The authors suggest that this view of endoderm differentiation, which doesn't require full EMT is novel, however, much of the observations here are already known. It is known that future endoderm cells do not down regulate E-Cadherin but instead must continue to express it. They also are known to migrate collectively rather than as single cells in a cadherin-dependent way (Montero et al., Development 2005; reviewed in Nowotschin et al., Development 2019). The authors should discuss this literature and make clear which aspects of the proposed mechanisms are novel.

The recent publication from the Lickert group, subsequent to our submission, does make the point that our observations and discussion were, and are, novel. With regard to the Montero, indeed, our observations are relevant, more so as they highlight aspects of endoderm specification in mammals that have not been described before and which shed light not only on endoderm specification in these embryos but to its relationship to anamniotes. We have now added a paragraph in the discussion to highlight this point and added two very relevant references.

3. The authors are assessing the status of EMT based on a single marker, E-Cad. If this is a major point of the manuscript other markers e.g. Snail, N-Cad should be examined.

We now provide N-cadherin and Snail staining in Figure 3 —figure supplements 3 and 4. N-Cad expression anti-correlates with E-Cad. E-Cad+ cells show either no Snail expression or extranuclear Snail. This second population corresponds to the sox2+ compact islands that segregate at the tip and become Sox17+.

4. It is well known that embryoid bodies form an outer layer of visceral endoderm e.g. Concouvanis and Martin Cell 1995, Doughton et al., PLOS One 2010. None of the markers here are exclusive to definitive endoderm (including Sox17 which is used throughout, see Artus et al., Dev Biol 2011). The authors should address the possibility that their observations may be consistent with a similar mechanism and may not reflect definitive endoderm differentiation.

As discussed before, Gastruloids are not Embryoid bodies and have already been shown not to have any visceral endoderm see e.g PMID: 28951435 and also discussion of reviewers comments in Vianello and Lutolf, bioRxiv 2021.

[Editors' note: further revisions were suggested prior to acceptance, as described below.]

Conceptual concern:

The notion that endoderm specification does not requite EMT is indeed backed up by data in the embryo, and this part is now adequately covered in the paper.

The observation that, in gastruloids, endoderm cells arise as islets that get sorted from the other cells possibly though differences in cell junctions tension is interesting and well substantiated. It is supported by studies in vitro in different species, including rather ancient experiments. However, the referees point that the evidence that a similar mechanism is at play in the mouse embryo is still weak, and would suggest tempering that claim (revise paragraph starting at line 233 in discussion).

We have shown that in the gastruloids, endoderm cells arise as islets that get sorted from other cells through surface tension difference. We tempered the claim that a similar mechanism is at play in vivo. The associated paragraph now reads:

“The evidence that a similar mechanism is at play in the mouse embryo remains partial, although a recent report suggests that endodermal progenitors emerge in small islands (see Figure 3 in (Probst et al., 2021))”.

Technical concern:

Although the reviewers acknowledge that the authors have increased the number of gastruloids and cells in most quantifications, they argue that the number is not huge yet in view of the variability. Therefore they propose that:

– number of samples and replicates should be added to the figure legends for clarity.

– statistical analysis should be reinforced through addition of a power calculation.

We are now reporting the number of samples and replicates in the figure legends and have also added power calculations (highlighted in yellow in the text).

Format:

Reviewers point that the paper would be better suited as a short report. A change of format at this stage may present a risk of losing clarity. We would nonetheless recommend to condense the data notably through fusion of the supplementary figures in one (or maximum two) per main figure.

We have reduced the number of figure supplements with a maximum of 2 figure supplements per main figure: 1 figure supplement for Figure 1, 2 figure supplements for Figure 2; 2 figure supplements for Figure 3; 2 figure supplements for Figure 4.

https://doi.org/10.7554/eLife.59371.sa2

Article and author information

Author details

  1. Ali Hashmi

    Aix-Marseille University, CNRS, UMR 7288, IBDM, Turing Center for Living Systems, Marseille, France
    Contribution
    Conceptualization, Formal analysis, Investigation, Methodology, Software, Writing - original draft, Writing - review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9946-7679
  2. Sham Tlili

    Aix-Marseille University, CNRS, UMR 7288, IBDM, Turing Center for Living Systems, Marseille, France
    Contribution
    Investigation, Methodology, Software, Writing - review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6018-9923
  3. Pierre Perrin

    Aix-Marseille University, CNRS, UMR 7288, IBDM, Turing Center for Living Systems, Marseille, France
    Contribution
    Investigation
    Competing interests
    No competing interests declared
  4. Molly Lowndes

    1. Novo Nordisk Foundation Center for Stem Cell Biology (DanStem), University of Copenhagen, Copenhagen, Denmark
    2. Novo Nordisk Foundation Center for Stem Cell Medicine (reNEW), University of Copenhagen, Copenhagen, Denmark
    Contribution
    Investigation, Resources
    Competing interests
    No competing interests declared
  5. Hanna Peradziryi

    Novo Nordisk Foundation Center for Stem Cell Biology (DanStem), University of Copenhagen, Copenhagen, Denmark
    Contribution
    Investigation, Resources
    Competing interests
    No competing interests declared
  6. Joshua M Brickman

    1. Novo Nordisk Foundation Center for Stem Cell Biology (DanStem), University of Copenhagen, Copenhagen, Denmark
    2. Novo Nordisk Foundation Center for Stem Cell Medicine (reNEW), University of Copenhagen, Copenhagen, Denmark
    Contribution
    Funding acquisition, Resources, Supervision
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1580-7491
  7. Alfonso Martínez Arias

    1. Department of Genetics, University of Cambridge, Cambridge, United Kingdom
    2. Systems Bioengineering, DCEXS , Universidad Pompeu Fabra, ICREA, Barcelona, Spain
    Contribution
    Conceptualization, Funding acquisition, Writing - review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1781-564X
  8. Pierre-François Lenne

    Aix-Marseille University, CNRS, UMR 7288, IBDM, Turing Center for Living Systems, Marseille, France
    Contribution
    Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Supervision, Writing - original draft, Writing - review and editing
    For correspondence
    pierre-francois.lenne@univ-amu.fr
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1066-7506

Funding

Agence Nationale de la Recherche (ANR-19-CE13-0022)

  • Pierre-François Lenne

Agence Nationale de la Recherche (ANR-11-LABX-0054)

  • Pierre-François Lenne
  • Ali Hashmi

Agence Nationale de la Recherche (ANR-16-CONV-0001)

  • Pierre-François Lenne
  • Sham Tlili

Agence Nationale de la Recherche (ANR-10-INBS-04)

  • Pierre-François Lenne
  • Sham Tlili
  • Ali Hashmi

Leverhulme Trust (VP2-2015-022)

  • Pierre-François Lenne
  • Alfonso Martínez Arias

Leverhulme Trust (RPG- 2018-356)

  • Pierre-François Lenne
  • Alfonso Martínez Arias

Lundbeckfonden (R198-2015-412)

  • Joshua M Brickman

European Research Council (AdG MiniEmbryoBlueprint 834580)

  • Alfonso Martínez Arias

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

The work is supported by the Leverhulme Trust (visiting professorship to PFL VP2-2015-022 and RPG-2018–356), Agence Nationale de la Recherche (“Investissements d’Avenir”, Labex INFORM Phd Grant to AH, ANR-11-LABX-0054 and ANR-16-CONV-0001 from Excellence Initiative of Aix-Marseille University - A*MIDEX and generic grant to PFL, ANR-19-CE13-0022), the Lundbeckfonden (Lundbeck Foundation, R198-2015-412). The Novo Nordisk Foundation Center for Stem Cell Medicine is supported by a Novo Nordisk Foundation grant (NNF21CC0073729). The Novo Nordisk Foundation Center for Stem Cell Biology was supported by a Novo Nordisk Foundation grant (NNF17CC0027852). We also acknowledge the France-Bioimaging Infrastructure (ANR-10-INBS-04). We thank Simone Probst and Sebastian Arnold for their advice. We are grateful to Rosanna Dono for her suggestions and help, and Tina Balayo for assistance with tissue culture. We thank all members of the Lenne and Martinez Arias groups. We thank Guillaume Blin, Sally Lowell and Val Wilson (CRG, University of Edinburgh) for sharing their cell line.

Senior Editor

  1. Didier YR Stainier, Max Planck Institute for Heart and Lung Research, Germany

Reviewing Editor

  1. Isabelle Migeotte, Université Libre de Bruxelles, Belgium

Reviewer

  1. Isabelle Migeotte, Université Libre de Bruxelles, Belgium

Publication history

  1. Preprint posted: May 24, 2020 (view preprint)
  2. Received: May 27, 2020
  3. Accepted: April 8, 2022
  4. Accepted Manuscript published: April 11, 2022 (version 1)
  5. Version of Record published: April 22, 2022 (version 2)

Copyright

© 2022, Hashmi et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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  1. Ali Hashmi
  2. Sham Tlili
  3. Pierre Perrin
  4. Molly Lowndes
  5. Hanna Peradziryi
  6. Joshua M Brickman
  7. Alfonso Martínez Arias
  8. Pierre-François Lenne
(2022)
Cell-state transitions and collective cell movement generate an endoderm-like region in gastruloids
eLife 11:e59371.
https://doi.org/10.7554/eLife.59371

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