Vascularized human cortical organoids (vOrganoids) model cortical development in vivo

Yingchao Shi; Le Sun; Mengdi Wang; Jianwei Liu; Suijuan Zhong; Rui Li; Peng Li; Lijie Guo; Ai Fang; Ruiguo Chen; Woo-Ping Ge; Qian Wu; Xiaoqun Wang

doi:10.1371/journal.pbio.3000705

. 2020 May 13;18(5):e3000705. doi: 10.1371/journal.pbio.3000705

Vascularized human cortical organoids (vOrganoids) model cortical development in vivo

Yingchao Shi ^1,^#, Le Sun ^1,^#, Mengdi Wang ^1,^2,^#, Jianwei Liu ^1,^#, Suijuan Zhong ², Rui Li ¹, Peng Li ¹, Lijie Guo ^1,³, Ai Fang ¹, Ruiguo Chen ^1,³, Woo-Ping Ge ⁴, Qian Wu ^2,^5,^*, Xiaoqun Wang ^1,^3,^6,^7,^*

Editor: Bing Ye⁸

¹State Key Laboratory of Brain and Cognitive Science, CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Brain-Intelligence Technology (Shanghai), Institute of Biophysics, Chinese Academy of Sciences, Beijing, China

²State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China

³University of Chinese Academy of Sciences, Beijing, China

⁴Children's Research Institute, University of Texas Southwestern Medical Center, Dallas, Texas, United States of America

⁵IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China

⁶Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, China

⁷Advanced Innovation Center for Human Brain Protection, Beijing Institute for Brain Disorders, Capital Medical University, Beijing, China

⁸University of Michigan, UNITED STATES

The authors have declared that no competing interests exist.

^✉

* E-mail: qianwu@bnu.edu.cn (QW); xiaoqunwang@ibp.ac.cn (XW)

Contributed equally.

Roles

Yingchao Shi: Data curation, Formal analysis, Validation, Writing – original draft, Writing – review & editing

Le Sun: Data curation, Formal analysis, Writing – review & editing

Mengdi Wang: Data curation, Formal analysis, Methodology, Writing – original draft, Writing – review & editing

Jianwei Liu: Formal analysis, Writing – review & editing

Suijuan Zhong: Data curation, Formal analysis, Writing – review & editing

Rui Li: Data curation, Writing – review & editing

Peng Li: Data curation, Writing – review & editing

Lijie Guo: Data curation, Formal analysis, Validation, Writing – review & editing

Ai Fang: Data curation, Writing – review & editing

Ruiguo Chen: Data curation, Writing – review & editing

Woo-Ping Ge: Supervision, Writing – review & editing

Qian Wu: Conceptualization, Data curation, Formal analysis, Funding acquisition, Supervision, Writing – original draft, Writing – review & editing

Xiaoqun Wang: Conceptualization, Funding acquisition, Supervision, Writing – original draft, Writing – review & editing

Bing Ye: Academic Editor

PMCID: PMC7250475 PMID: 32401820

Abstract

Modeling the processes of neuronal progenitor proliferation and differentiation to produce mature cortical neuron subtypes is essential for the study of human brain development and the search for potential cell therapies. We demonstrated a novel paradigm for the generation of vascularized organoids (vOrganoids) consisting of typical human cortical cell types and a vascular structure for over 200 days as a vascularized and functional brain organoid model. The observation of spontaneous excitatory postsynaptic currents (sEPSCs), spontaneous inhibitory postsynaptic currents (sIPSCs), and bidirectional electrical transmission indicated the presence of chemical and electrical synapses in vOrganoids. More importantly, single-cell RNA-sequencing analysis illustrated that vOrganoids exhibited robust neurogenesis and that cells of vOrganoids differentially expressed genes (DEGs) related to blood vessel morphogenesis. The transplantation of vOrganoids into the mouse S1 cortex resulted in the construction of functional human-mouse blood vessels in the grafts that promoted cell survival in the grafts. This vOrganoid culture method could not only serve as a model to study human cortical development and explore brain disease pathology but also provide potential prospects for new cell therapies for nervous system disorders and injury.

This study establishes a method to generate vascularized cortical organoids. This shows that in addition to reducing hypoxia and cell death, the vascular system promotes neural development in organoids. When transplanting these organoids into host mice, a graft-host vascular system could be reconstructed.

Introduction

In contrast to the rodent lissencephalic cortex, the human neocortex has evolved into a highly folded gyrencephalic cortex with enormous expansion of the cortical surface and increases in cell type and number [1,2]. Animal models, particularly rodents, have provided significant insight into brain development, but the complexity of the human neocortex cannot be fully captured with these models. Therefore, understanding the genetic changes as well as the mechanistic steps that underpin the evolutionary changes that occur during the development of the neocortex in primates may require new model systems.

Organoids have recently been used to study the development of and pathological changes in different tissue types, such as pancreas, liver, kidney, and retina tissues [3–8]. In addition, several different methods involving the differentiation of human-induced pluripotent stem cells (hiPSCs) have been developed to generate organoids that mimic nervous system development [9–19]. Three-dimensional brain organoids are comprised of multiple cell types that collectively exhibit cortical laminar organization, cellular compartmentalization, and organ-like functions. Therefore, compared to conventional 2D culture, organoids are advantageous because they can recapitulate embryonic and tissue development in vitro and are better at mirroring the functionality, architecture, and geometric features of tissues in vivo.

Previous studies have successfully established suitable approaches for generating cerebral organoids from human embryonic stem cells (hESCs) or hiPSCs that can recapitulate in vivo human cortical development and a well-polarized ventricle neuroepithelial structure that consists of ventricular radial glia (vRGs), outer radial glia (oRGs), and intermediate progenitor cells (IPCs) and the production of mature neurons within layers [12,13,15,17,18,20]. However, a major limitation of current culture approaches that prevents truly in vivo–like functionality is the lack of a microenvironment, such as vascular circulation. Previous studies have reported that the development of the nervous system and the vascular system in the brain is synchronous [21–23]. Vascularization is specifically required for oxygen, nutrient, and waste exchange and for signal transmission in the brain. Additionally, blood vessels around neural stem cells (NSCs) serve as a microenvironment that maintains homeostasis, and they play essential roles in NSC self-renewal and differentiation during embryonic development [24,25]. A lack of vascular circulation can induce hypoxia during organoid culture and accelerate necrosis, which consequently hinders the normal development of neurons and their potential migration [26]. To overcome these limitations, some studies have tried to generate vascularized organoids (vOrganoids) by coculturing hESC- or hiPSC-derived cerebral organoids with endothelial cells (ECs) differentiated from induced pluripotent stem cells (iPSCs) from the same patient [27]. In addition, recent studies have established a robust method for generating vascularized human cortical organoids by introducing hESCs that ectopically express ETV2 into organoids [28]. Mansour and colleagues showed that transplanting human cerebral organoids into the adult mouse brain can result in the formation of a vascularized and functional brain organoid model in vivo [29]. In addition, other reports have demonstrated that compared to transplanting dissociating neural progenitor cells, engrafting cerebral organoids into the lesioned mouse cortex induces enhanced survival and robust vascularization [30]. All of these studies indicate that vascularization is one of the feasible methods to improve organoid survival. In addition to the methods reported in these studies, other stable and reproducible methods are required for establishing vascularized cerebral organoids to model human brain development in vitro and to perform in vivo transplantation.

Here, we developed a 3D culture protocol to generate vOrganoids by coculturing hESCs or hiPSCs with human umbilical vein endothelial cells (HUVECs) in vitro. In our studies, HUVECs were connected and formed a well-developed mesh-like or tube-like vascular system in the cerebral organoids. vOrganoids recapitulated neocortical development, exhibiting different cell types and a neural circuit network, in vitro. In addition, single-cell RNA sequencing (scRNA-seq) analysis verified that vOrganoids shared similar molecular properties and cell types with the human fetal telencephalon. Finally, we intracerebrally implanted vOrganoids into mice and observed that the grafted vOrganoids survived and integrated into the host cortical tissue in vivo. Importantly, the vessels in vOrganoid grafts connected well with the native blood vessels in the rodents to build a new functional vascularization system. This vOrganoid culture system serves as a model for studying human cortical development and provides new potential therapeutic strategies for treating brain disorders or injuries.

Results

Vascularization in the 3D vOrganoid culture system

HUVECs, which are derived from the endothelium of veins from the umbilical cord, have been widely used to explore the function and pathology of ECs [31–33]. In addition, via coculturing with other cell types, HUVECs have been extensively used to characterize angiogenesis during tumorigenesis and other biological processes [34–36]. Due to the tube formation ability of HUVECs (S1A Fig), we generated vascularized cerebral organoids by coculturing hESCs or hiPSCs with HUVECs. Approximately 3 × 10⁶ dissociated hESCs or hiPSCs and 3 × 10⁵ HUVECs were plated onto low cell-adhesion plates, and uniformly sized tight embryoid body-like aggregates formed within the first 7 days. On day 18, the aggregates were transferred to petri dishes for neural induction culture. The resulting 3D aggregates were then replated for neural differentiation on day 35. Nonvascularized control organoids were generated by the same workflow except that no HUVECs were added (Fig 1A). vOrganoids differentiated and matured for up to approximately 200 days under the optimized culture conditions (Fig 1B, 1G and 1L).

(A) Schematic diagram of the 3D culture methods for generating cerebral organoids with complicate vascular systems. (B) Representative bright field (BF) images of vOrganoids at different stages. Scale bar, 200 μm. (C) Whole mount imaging of vOrganoid on day 42. The elaborate mesh-like vascular systems in vOrganoids were displayed by immunofluorescence staining for LAMININ and IB4. Areas 1 and 2 outlined in boxes were magnified and reconstructed in 3D to depict the complexity of vasculature in vOrganoids. Scale bar, 100 μm (upper left), 50 μm (in box 1), 50 μm (in box 2). The arrowheads pointed out the hollows in the vascular systems that are permeable at different views. (D) Representative immunofluorescence staining figure for TBR2, SOX2, and IB4 to reveal that the vasculogenesis in vOrganoids is synchronous to the neurogenesis at early stage. Scale bar, 50 μm. (E) Representative immunofluorescence staining figure for HOPX, SOX2, and IB4 to demonstrate that the HOPX⁺ SOX2⁺oRG cells could be detected in the vOrganoids at day 65. Scale bar, 50 μm. (F) Representative immunofluorescence staining figure for CTIP2/IB4/PAX6 at day 65 to demonstrate that the IB4⁺ vascular structures would progressively extend into newborn neurons (CTIP2⁺) with the development of vOrganoids. Scale bar, 50 μm. (G) Representative IB4 and LAMININ staining figure in vOrganoid at day 210 to demonstrate that the vascular system could be maintained for over 200 days. Scale bars, 100 μm. (H) The spatial organization of vOrganoids was illustrated by immunofluorescence staining for TBR2/CTIP2 (left panel) and SATB2/CTIP2 (right panel) at day 65. Scale bar, 50 μm. (I) Representative immunofluorescence staining figure for the SATB2 and SOX2 to illustrate that SATB2⁺ cells are mainly located above the SOX2⁺ progenitor cells (left panel); SST and CR staining illustrated the emergence of interneurons in vOrganoids at day 65 (right panel). The “#5” and “#6” labelled in the upper left represent the number of continuous sections of vOrganoids. Scale bars, 50 μm. (J-L) Representative immunostaining figure for the pyramidal layer markers and interneuron markers in the continuous cryosections of vOrganoids at day 92 (J), day 128 (K), and day 210 (L). Scale bars, 50 μm. (M) The percentage of SATB2⁺, BRN2⁺, and CTIP2⁺ cells in the vOrganoids of day 128 and day 210, respectively. n = 3 organoids from three independent experiments. All data are presented as means ± SEM, independent-samples t test, *p < 0.05, **p < 0.01. The numerical data underlying this figure can be found in the Fig 1M sheet of S1 Data. BRN2, POU class 3 homeobox 2; CR, calretinin; CTIP2, chicken ovalbumin upstream promoter transcription factor (COUP-TF)–interacting protein 2; EB, embryonic body; hESC, human embryonic stem cell; hiPSC, human-induced pluripotent stem cell; HOPX, homeodomain only protein X; IB4, isolectin I-B4; iPSC, induced pluripotent stem cells; oRG, outer radial glia; PAX6, paired box 6; SATB2, SATB homeobox 2; SOX2, SRY-box transcription factor 2; SST, somatostatin; TBR2, eomesodermin; vOrganoid, vascularized organoid.

To visualize vascularization in vOrganoids, LAMININ, the major basement membrane glycoprotein of blood vessels, and isolectin I-B4 (IB4), a marker of ECs, were both used. We observed that the HUVECs connected to form a mesh-like and tube-like structure in vOrganoids as early as 42 days (Fig 1C and S1B Fig, S1 Movie and S2 Movie). Previous studies have confirmed that the proliferating cells in the ventricular zone/subventricular zone (VZ/SVZ) are, on average, closer to blood vessels [37,38]. Interestingly, in our studies, vascularization in vOrganoids primarily occurred just above the VZ/SVZ region, which is enriched with SRY-box transcription factor 2 (SOX2)⁺ radial glia cells (RGs), homeodomain only protein X (HOPX)⁺ oRGs, and eomesodermin (TBR2)⁺ IPCs (Fig 1D and 1E). Meanwhile, some vessels were also detected in the migrating zone and cortical plate (CP; Fig 1D). This localization and distribution were similar to those of blood vessels in the developing human cerebral cortex at gestational week (GW) 12 (S1C Fig). As vOrganoids developed up to day 65, the vascular structures extended into newborn neurons (Fig 1F). The vascular system, mainly located in the outer layers of vOrganoids, which were enriched with neurons, was sustained for over 200 days (Fig 1G).

To test whether the ability of the culture protocol to produce vascular systems in organoids is reproducible in different cell lines, vOrganoids were cultured from two hESC cell lines (H9 and H3) and two hiPSC cell lines (hiPSCs-AE and hiPSCs-LMZ). vOrganoids derived from the different cell lines exhibited similar vascular structures in similar locations (S1D and S1E Fig), indicating the reproducibility of the culture protocol. The vascularization success rate in H9 cells was 100% over more than 30 experiments, while the success rates in the other three cell lines were higher than 95% in at least 3 biological replicates for each. Then, we performed cleaved CASPASE 3 immunostaining in nonvascularized organoids and vOrganoids and found that the cell ratio of cleaved CASPASE 3⁺ cells in vOrganoids was significantly reduced compared to that in nonvascularized organoids (S1F Fig, upper panel; and S1G Fig). In addition, we also performed immunostaining for hypoxia induciable factor 1 subunit alpha (HIF1α), which is a hypoxia marker. Consistent with the results of cleaved CASPASE 3 staining, the cell ratio of HIF1α-positive cells in the vOrganoids was significantly reduced (S1F Fig, lower panel, and S1G Fig). The HIF1α-positive cells in vOrganoids were mainly located in the center of the organoids, while those in nonvascularized organoids were abundant and widespread (S1F Fig, lower panel). Moreover, vOrganoids were larger in size and possessed thicker neuroepithelia than nonvascularized organoids (S1H–S1K Fig). These results indicate that the vascular systems in vOrganoids may provide more oxygen to support cell survival, resulting in decreased cell death and larger vOrganoids. Human brain microvascular endothelial cells (HBMECs) are the main ECs in the human brain and play important roles in the development of the blood–brain barrier (BBB) [39]. Given the difference between HUVECs and HBMECs, we also examined whether coculture can induce HUVECs to adopt a more brain-like EC fate. P-glycoprotein (P-gp), an efflux transporter that influences the absorption, distribution, and elimination of a variety of compounds, has been reported to be expressed on brain capillary ECs. In our studies, P-gp was abundantly detected in brain capillary ECs at GW12 but not in cultured HUVECs (S1L Fig and S1M Fig). These results indicate that when cultured individually in the absence of organoids, HUVECs can form tube-like structures that are similar to those in vOrganoids, but do not express P-gp (S1M Fig). Next, we examined the expression of P-gp in the vOrganoids on day 83. The high degree of IB4 and P-gp colocalization in vOrganoids (S1N Fig) indicated that coculture might induce HUVECs to adopt a more brain-like EC fate.

Recapture of cell subtypes during neurogenesis

To determine whether vOrganoids can recapitulate human cortical organization (S1O Fig), we stained for cortical layer markers on day 65. We found that TBR2⁺ IPCs were adjacent to the early CP, which was indicated by chicken ovalbumin upstream promoter transcription factor (COUP-TF)–interacting protein 2 (CTIP2)⁺ cells (Fig 1H, left panel). Furthermore, we found that some SATB homeobox 2 (SATB2)⁺ cells were superficially localized to CTIP2⁺ neurons and some were widely distributed in the migrating zone and newly formed CPs in vOrganoids (Fig 1H, right panel; Fig 1I, left panel; and S1P Fig). This observation was consistent with reports showing that SATB2 is expressed by virtually all upper layer projection neurons as well as 30% of deep layer neurons that project through the corpus callosum [40–42]. In addition, we also observed that early-born reelin (RELN)⁺ cells were located in the superficial layer while later-born TBR1⁺ cells were located in the deeper layer (S1Q Fig).

Because pyramidal neurons and interneurons are both required to form neural circuits, we also paid close attention to the different subtypes of interneurons in vOrganoids. Calretinin (CR)⁺ or somatostatin (SST)⁺ cells were first detectable at day 65 in continuous sections of vOrganoids (Fig 1I, right panel). Moreover, layer-specific pyramidal neurons were surrounded by sparse interneurons in the late stages of the 3D culture on days 92, 128, and 210 (Fig 1J–1L). The proportion of upper layer neurons increased from 15.94% to 33.04% from day 128 to day 210, and the interneurons were sparsely distributed (Fig 1K–1M), indicating that the vOrganoid culture system models the organization of the neocortex in vivo.

Next, we used scRNA-seq (10X Genomics Chromium) to capture the cellular and molecular features of the vOrganoids. We collected nonvascularized organoid and vOrganoid samples at two time points: day 65 and day 100 (Fig 2A and 2B and S2A Fig). There were three independent experimental replicates for each group (S2A Fig). After quality control, we obtained a final dataset of 57,180 cells from 12 independent samples encompassing an average of 2,762 genes per cell (S2B Fig, S1 Table). To characterize the cellular heterogeneity of vOrganoids and nonvascularized organoids, we performed Uniform Mainfold Approximation and Projection (UMAP) analysis with Seurat (Stuart and colleagues, 2019) and identified 11 major clusters, including RGs, oRGs, IPCs, cell cycle active cells (labeled as cell cycle), immature neurons, excitatory neurons, interneurons, microglia, astrocytes, oligodendrocyte progenitor cells (labeled as OPCs) and choroid plexus cells, based on the expression of classical gene markers (Fig 2A, S2C and S2D Fig, and S1 Table). The high transcriptomic correlations between the corresponding cell types in the organoids suggested that there are no remarkable cell type differences between nonvascularized organoids and vOrganoids (S2E Fig).

(A) Visualization of the major cell types in organoids and vOrganoids by 3D UMAP. Each dot represents one individual cell and colored by cell types. The expression of known gene markers was visualized at the lower panel and cells were colored by the expression level (red, high; gray, low). (B) The cell distributions of control organoids and vOrganoids at d65 and d100, respectively, were individually showed using UMAP. Each dot represents one individual cell and colored by sample information. (C) The scRNA-seq data of organoids and human fetal telencephalon were integrated to display the cell similarities in forced-directed graph. The integrated data were showed in the top left zoomed-out plot. Meanwhile, the cell distributions of organoids and human fetal telencephalon were highlighted separately. Each dot represents a single cell and is colored according to the cell types in the integrated data. The width of edges is scaled with cell–cell connectivity. (D) The correlations among cell types are displayed in the PAGA graph. The cell types in the organoids and human fetal cortex datasets were denoted by the solid and hollow dots, respectively. And the same cell types in two datasets were colored identically. The size of dots was scaled with the cell numbers; width of edges was scaled with the connectivity between cell types. (E) The expression of the well-known gene markers in different cell types is showed in the PAGA plots. The GAD1, NEUROD2, EOMES, and AIF1 are the specific genes for interneuron, excitatory neurons, IPCs, and microglia, respectively. Nodes are colored according to the gene expression levels (light pink, low; dark red, high). (F) The fitted curves of cell density along the pseudo-time at day 65 (upper) and day 100 (lower) The shadow represents the confidence interval around the fitted curve. (G) The curves of cell density along the pseudo-maturation trajectory at day 65 (upper) and day 100 (lower). The shadow represents the confidence interval around the fitted curve. (H) Immunofluorescence staining for NEUROD2/IB4 in the control organoids and vOrganoids at day 65. The expressions of NEUROD2 are individually displayed in the right panel. Scale bar, 100 μm. (I) The ratio of NEUROD2⁺ excitatory neurons is higher in the vOrganoids than in the control organoids at day 65. n = 4, 4 control organoids and vOrganoids from three independent experiments. (J) Heatmap showing the expression of DEGs between the progenitor cells (included RG, oRG, cell cycle active cells, and IPCs) of control organoids and vOrganoids at day 65. The enriched gene ontology of the DEGs and the adjusted p-values are also listed. (K) Representative immunofluorescence staining figure for AIF1, a specific microglia marker, to illustrate the presence of microglia in organoids. Scale bar, 10 μm (left), 5 μm (right). (L) Immunofluorescence staining for GFAP to illustrate the presence of astrocytes in organoids. Scale bar, 10 μm. (M) A few of NKX2-1–positive cells are detected in the immunofluorescence staining section. The area in the white dashed box is magnified in the lower panel. Scale bar, 200 μm (upper), 20 μm (lower). The numerical as well as metadata underlying this figure can be found in the Fig 2A, 2B, 2C and 2I sheets of S1 Data. AIF1, allograft inflammatory factor 1; Ast, astrocyte; cell cycle, cell cycle active cell; Ch, choroid plexus; DEG, differentially expressed gene; Endo, endothelial cell; EOMES, eomesodermin; ExN, excitatory neuron; GAD1, glutamate decarboxylase 1; GFAP, glial fibrillary acidic protein; IB4, isolectin I-B4; ImN, immature neuron; IN, interneuron; IPC, intermediate progenitor cell; MGE, medial ganglionic eminence; MGE-div, MGE dividing cell; Mic, microglia; Mural, mural cell; NEUROD2, neuronal differentiation 2; NKX2-1, NK2 homeobox 1; OPC, oligodendrocytes progenitor cell; oRG, outer radial glia; PAGA, partition-based graph abstraction; RG, radial glia cell; scRNA-seq, single-cell RNA sequencing; UMAP, Uniform Mainfold Approximation and Projection; vOrganoid, vascularized organoid.

We then aimed to compare the similarities between the organoids and the human fetal telencephalon at the single-cell level [43]. To identify the homologous cell types between organoids and primary tissue, we integrated organoid cells and embryonic human telencephalon cells and found that the same cell types were generally close to each other (Fig 2C). To clearly exhibit the correlations of cell types between organoids and human telencephalon, we constructed a correlation network via partition-based graph abstraction (PAGA) (Fig 2D and 2E and S2F Fig). In the PAGA plots, the RGs, oRGs, IPCs, excitatory neurons, interneurons, astrocytes, microglia, choroid plexus cells, and OPCs in the organoids were located close to the corresponding cell types in the human telencephalon (Fig 2D and 2E and S2F Fig). These results suggest that based on transcriptome analysis, the cell types in organoids are highly similar to the corresponding cell types in the human fetal telencephalon.

To explore whether vOrganoids more closely recapitulate fetal telencephalon development than control organoids, we compared the single-cell transcriptome profile of the human fetal telencephalon with that of control organoids (S2G and S2H Fig) and vOrganoids (S2I and S2J Fig) separately. Based on PAGA as well as transcriptomic correlation analysis, the cell types in control organoids as well as those in vOrganoids were highly similar to those in the human fetal telencephalon (S2K–S2N Fig). Although there were no obvious differences in cell types or the similarity to the human fetal telencephalon between vOrganoids and control organoids, we then compared the development of vOrganoids and nonvascularized organoids by analyzing the scRNA-seq data. First, we predicted the developmental states of the cells in control organoids and vOrganoids along the pseudo-time trajectory by monocle analysis [44–46]. The fitted curves of the cell density along the pseudo-time were plotted on day 65 and day 100 (Fig 2F). More vOrganoid cells than nonvascularized organoid cells were assigned a high pseudo-time score (Fig 2F). The extent of divergence was more obvious on day 65 than on day 100 (Fig 2F). These results indicate that vOrganoids develop faster than nonvascularized organoids, even though this difference decreases during development. To further validate this observation, we calculated the maturation score of each cell in vOrganoids and controls (Fig 2G). Similar to the developmental pseudo-time analysis, there were fewer vOrganoid cells than nonvascularized organoid cells with low maturation scores and more vOrganoid cells than nonvascularized organoid cells with high scores (Fig 2G). Together, both the developmental state and maturation trajectory analyses suggest that the vascular systems in vOrganoids might accelerate the development of vOrganoids in the early stage.

Next, to understand why vOrganoids develop faster than control organoids, we analyzed the cell composition on day 65. We found that the percentage of one type of neural progenitor cell—oRGs—was much higher in vOrganoids than in nonvascularized organoids (S2O Fig). oRGs originate from RGs and play important roles in neurogenesis, greatly contributing to rapid excitatory neuron production during human fetal cortical development [47,48]. Accordingly, the percentage of excitatory neurons, the progenies of neural progenitor cells, in vOrganoids was much higher than that in nonvascularized organoids on day 65 (S2O Fig). Consistently, more neuronal differentiation 2 (NEUROD2)+ neurons were detected in vOrganoids than nonvascularized organoids by immunostaining on day 65 (Fig 2H and 2I). Thus, both scRNA-seq and immunostaining suggested that the vascular systems in vOrganoids may promote neurogenesis in vitro.

Given the intimate interactions between the vasculature and proliferative progenitor cells during brain development [49–52], we also attempted to detect whether the vascular systems in vOrganoids can influence gene expression in neural progenitors. We conducted the differentially expressed gene (DEG) and Gene Ontology (GO) enrichment analysis of progenitors (cell cycle active cells, RGs, oRGs, and IPCs) in vOrganoids and nonvascularized organoids. The GO terms enriched in progenitor cells in nonvascularized organoids were responses to hypoxia and positive regulation of cell death (Fig 2J, S1 Table). These GO terms are consistent with the higher number of HIF1α⁺ and cleaved CASPASE 3⁺ cells observed in nonvascularized organoids (S1F and S1G Fig). Meanwhile, the GO terms enriched in progenitor cells in vOrganoids were positive regulation of neurogenesis and blood vessel morphogenesis (Fig 2J, S1 Table).

In addition to neurons, we also detected glial cells, such as microglia, OPCs, and astrocytes, in our scRNA-seq dataset (Fig 2A). We performed immunostaining for microglia-specific allograft inflammatory factor 1 (AIF1) and astrocyte-specific glial fibrillary acidic protein (GFAP) and verified the presence of these markers in vOrganoids (Fig 2K and 2L). In addition, we detected interneurons with high expression of glutamate decarboxylase 1 (GAD1)/distal-less homeobox 1 (DLX1) and sparse expression of NK2 homeobox 1 (NKX2-1) and LIM homeobox 6 (LHX6) in our scRNA-seq data (Fig 2A and S2C Fig). The immunostaining results also illustrated sparsely distributed NKX2-1⁺ cells in vOrganoids (Fig 2M). Notably, we also detected a cluster of choroid plexus epithelial cells, which displayed transcriptomic similarity with the choroid plexus in the human telencephalon (Fig 2A, S2C Fig and S2F Fig). In vivo, the choroid plexus is mainly responsible for the production of cerebrospinal fluid (CSF), which serves as a rich source of proteins, lipids, hormones, cholesterol, glucose, microRNA, and many other molecules for the maintenance of central nervous system (CNS) functions and plays a role in embryonic neurogenesis [53].

Modeling functionality maturation during neurogenesis

Several previous studies have illustrated that neurons in cortical organoids without vascular structures are ultimately able to reach mature states as their morphology and functionality progressively mature [13,20,54]. Because vOrganoids partially recapitulate human cortical development based on gene expression and cell subtypes, we next investigated the functional characteristics of the neurons by obtaining electrophysiological recordings. We performed patch-clamp recordings on slices from both control organoids and vOrganoids. To unbiasedly record neurons in vOrganoids and nonvascularized organoids, we selected neurons with similar soma diameters (S3A Fig) located within 150 μm of the edge of the organoid slices (S3B Fig). There were no differences in the amplitude of the inward currents. However, dramatic increases in outward current amplitudes were found in vOrganoid cells on day 80 (Fig 3A and 3B and S3C Fig). The increased outward current might in turn contribute to higher firing ability under current stimulation of different amplitudes in vOrganoids compared to nonvascularized organoids (S3D and S3E Fig). Because outward current increases significantly during the maturation process of cortical neurons [55], our observations suggest that neurons in vOrganoids might be more mature than those in nonvascularized organoids. Apart from increased outward current, vOrganoid neurons also exhibited lower resting membrane potential (S3F Fig) and greater cell capacitance (S3G Fig), suggesting that there might be increased dendritic or axonal growth in vOrganoids. Additionally, more spontaneously active cells were detected in vOrganoids (8/56 cells) than in nonvascularized organoids (4/52 cells) on day 80 (S3H Fig). Together, these results indicate that the vascular system in vOrganoids may accelerate the progression of the functional development of individual neurons in vitro.

(A) The amplitudes of outward (upper) and inward (lower) currents from the organoids (black) and vOrganoids (red) cells at day 60 (32 cells from 5 organoids in 4 independent experiments; 53 cells from 8 vOrganoids in 6 independent experiments), day 80 (45 cells from 6 organoids in 4 independent experiments; 49 cells from 6 vOrganoids in 4 independent experiments, p-values: 0.0428, 0.0278, 0.0222, 0.0171, 0.0085, 0.0066, 0.0072, 0.0099, and 0.0131 when evoked voltages are −20, −10, 0, 10, 20, 30, 40, 50, and 60 mV) and day 90 (42 cells from 6 organoids in 4 independent experiments; 50 cells from 6 vOrganoids in 5 independent experiments, p-values: 0.0090, 0.0027, 0.0033, 0.0025, and 0.0018 when evoked voltages are 20, 30, 40, 50, and 60 mV). Two-sample t test, data shown as mean ± SEM, *p < 0.05, **p < 0.01, ***p < 0.001. (B) The amplitudes of outward currents elicited by +60 mV (indicated by gray box in upper panel of A) and the amplitudes of inward currents elicited by −10 mV (indicated by gray box in lower panel of A) from organoid (black) and vOrganoid (red) cells at day 60, day 80, and day 90. Open circles indicate the amplitude of current from individual cells. Filled circles indicate the mean value. p-Values: 0.0108 (outward current of vOrganoid d60 versus d80), 0.0615 (outward current of vOrganoid d80 versus d90), 0.0131 (outward current at day 80 organoid versus vOrganoid), 0.0018 (outward current at day 90 organoid versus vOrganoid), 0.0066 (inward current of organoid d60 versus d80), 0.00001 (inward current of vOrganoid d60 versus d80). Two-sample t test, data shown as mean ± SEM, *p < 0.05, **p < 0.01, ***p < 0.001. (C-F) Spontaneous EPSCs (C) and IPSCs (E) were recorded in vOrganoids. The average frequency and amplitude of EPSCs and IPSCs are shown in (D) and (F), respectively. n = 6, 6 cells from 3 organoid and 3 vOrganoids in three independent experiments for sEPSCs (D) and sIPSCs (F), respectively. (G) Synapses in vOrganoids are revealed by immunofluorescence staining for the pre- and postsynaptic markers, SYB2 and PSD95, respectively. Scale bar, 10 μm. (H) Intracellular spontaneous calcium fluctuations were measured before and after the application of TTX, CNQX, APV, and BMI in the vOrganoids at day 50 and day 85, respectively. (I) The effects of different treatments on spontaneous calcium fluctuations were compared between day 50 and day 85 in the statistical results. Relative Ca2⁺ transient frequencies are normalized with the ACSF data of day 50. There are 188 and 124 cells in total for day 50 and day 85. All data are presented as means ± SEM. n = 188, 124, 31, 9, 65, 33, 77, 36, 15, and 46 from three independent experiments. Two-sample t test, p_ACSF = 0.1266, p_TTX = 0.2798, p_CNQX = 0.0208, p_APV = 0.00005, p_BMI = 0.0075. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. (J) Coupling pattern was visualized by cell injection. Green arrows indicated the injected cells. Red arrows indicated the cells that were connected to the injected cells. Scale bar, 50 μm. (K-L) The gap junctions between two cells (CMV-GFP labeled) were identified by dual-patch recording. The morphology of cells that dual patched was showed in (K). Scale bar, 50 μm in (K). The voltage deflections with small amplitudes were recorded in one cell while currents were injected into the other cell (L). The numerical data underlying this figure can be found in the Fig 3A, 3B, 3D, 3F and 3I sheets of S1 Data. ACSF, artificial cerebral spinal fluid; APV, DL-2-Amino-5-phosphonopentanoic acid; BMI, bicuculline methiodide; CMV, cytomegalovirus; CNQX, 6-Cyano-7-nitroquinoxaline-2,3-dione; DGC, dodt gradient contrast; GFP, green fluorescent protein; PSD95, postsynaptic density protein-95; sEPSC, spontaneous excitatory postsynaptic current; sIPSC, spontaneous inhibitory postsynaptic current; SYB2, synaptobrevin 2; TTX, tetrodotoxin; vOrganoid, vascularized organoid.

To build coordinated neural circuits, individual neurons must establish synaptic connections with each other. Therefore, we next focused on the formation of synapses in the vOrganoids. We recorded spontaneous excitatory postsynaptic currents (sEPSCs) and sIPSCs from vOrganoids from day 90 to day 100 (Fig 3C–3F), and sIPSCs were blocked by the gamma-aminobutyric acid A (GABAA) receptor antagonist bicuculline methiodide (BMI) (S3I Fig). Furthermore, to monitor the formation of the synapses, staining for synaptobrevin 2 (SYB2) and postsynaptic density protein-95 (PSD95) was performed to identify presynapses and postsynapses, respectively. We found abundant SYB2⁺ and PSD95⁺ puncta, some of which were colocalized, in vOrganoids on day 62 (Fig 3G). On day 210, dense distribution of RNA binding fox-1 homolog 3 (NeuN)⁺/microtubule associated protein 2 (MAP2)⁺ mature neurons was observed (S3J Fig), and Na⁺ currents and sIPSCs/sEPSCs were captured from these mature neurons (S3K–S3M Fig), which was indicative of long-standing synaptic formation in vOrganoids.

Intracellular calcium fluctuation imaging is an efficient method for characterizing the functional features of neural activities in cortex-like organoids. Therefore, we performed calcium dye imaging to detect calcium oscillations and observed spontaneous calcium surges in individual cells. When we blocked the action potentials with the application of tetrodotoxin (TTX), a specific blocker of voltage-gated sodium channels, we observed dampened calcium surges in most cases, indicating that spontaneous calcium events in neurons depend on neuronal activity (Fig 3H and S3N Fig). To further characterize the types of mature neurons, we applied exogenous glutamate and observed more frequent calcium events, indicating that these neurons exhibited glutamatergic receptor activity on day 85 (S3O Fig). Given the predominance of glutamatergic neurons in the aggregates, we combined a pharmacological assay with calcium imaging to further illustrate the differences in receptor-mediated synaptic transmission on day 50 and day 85. Neuronal activity in vOrganoids was reduced during treatment with DL-2-Amino-5-phosphonopentanoic acid (APV), which is an N-methyl-D-aspartate (NMDA) receptor antagonist, 6-Cyano-7-nitroquinoxaline-2,3-dione (CNQX), which is an α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor antagonist, or BMI, which is a GABAA receptor antagonist, indicating that NMDA receptor–, AMPA receptor–, and GABAA receptor–mediated synaptic activities were present after day 50 (Fig 3H and 3I). Importantly, when we compared neurons on day 50 and day 85, we observed reduced sensitivity to APV and greater sensitivity to CNQX on day 85 (Fig 3I), which indicated a transition from NMDA receptor–to AMPA receptor–mediated excitatory synaptic activity during the integration and maturation of vOrganoids. This is similar to what happens in vivo [56]. We also observed that BMI severely reduced neural activity on day 50 but not on day 85 (Fig 3H and 3I), indicating that the GABAergic response changed from depolarizing to hyperpolarizing during development; this change can be induced by a decreased intracellular chloride ion concentration due to the expression of potassium-chloride transporter member 5 (KCC2) [57].

In addition to the formation of chemical synapses, we also investigated the formation of electrical synapses (gap junctions) in vOrganoids. To identify the connectivity of the neural network, we explored how many cells were connected to one neuron through gap junctions. When we injected neurobiotin into two neurons, 11 coupled neurons were observed (Fig 3J and S3P Fig), suggesting that electrical connections exist in vOrganoids. To directly observe electrical coupling between neurons, we performed dual-patch recordings of vOrganoids. When the dual patch was established, voltage deflections with small amplitudes were recorded from one cell while currents were injected into the other cell (Fig 3K and 3L). Bidirectional electrical transmission indicated the existence of gap junctions between these two cells (Fig 3L). Together, these results indicate that the neurons in vOrganoids can become functionally mature with the emergence of a spontaneous action potential and that functionally mature neurons can later connect to one another based on the formation of abundant chemical and electrical synapses and receptor maturation.

Transplantation of vOrganoids reconstructs the vascular system in the mouse cortex

The long-term survival of organoid grafts in a host requires vascularization to satisfy the adequate delivery of oxygen and nutrients. The intracerebral implantation of hiPSC-derived brain organoids into the retrosplenial cortex of immunodeficient mice results in the recruitment of mouse blood vessels that grow into the grafts and support the long-term survival of the cells [29]. Therefore, we next tested whether the vascular systems in the vOrganoids can connect to blood vessels in the brain of the host to build a functional circulatory system. Sixty-day-old vOrganoids were intracerebrally implanted into a cavity that was made in the S1 cortex of nonobese diabetic severe combined immunodeficient (NOD-SCID) mice (Fig 4A). At 60 days postimplantation (dpi), we observed the integration of the organoid grafts into the host brain tissue (Fig 4B). SATB2⁺ cells were generally distributed close to the surface even though sometimes interrupted by SATB2⁻/CTIP2⁻ VZ-like rosettes. Meanwhile, CTIP2⁺ cells were mainly located in the deep area of the grafts (Fig 4B).

Fig 4 — **(A)** Schematic diagram to demonstrate the vOrganoids implantation protocols in our studies. The vOrganoids were transplanted into the S1 cortex of NOD-SCID mice. **(B)** Representative immunofluorescence staining figure for the classical cortical layer markers, CTIP2 and SATB2, at 2 months postimplantation. The boxed area was magnified in the right panel. Scale bar, 500 μm (left), 50 μm (right). **(C)** Representative immunofluorescence staining figure for presynaptic (SYB2) and postsynaptic (PSD95) in the vOrganoid grafts of 60 dpi. The displayed area was close to the graft–host border. The colocalization (arrowheads) and close association of SYB2 and PSD95 indicate that synaptic connectivity emerges in the organoid grafts. Scale bar, 10 μm. **(D)** The blood vessels in the vOrganoid grafts were reconstructed in three dimensions. The red tubular structure was blood vessels. Scale bar was labeled at three dimensions. Scale bar, 30 μm. **(E)** Immunofluorescence staining for LAMININ, dextran, and HUN were performed to confirm that the human ECs derived from vOrganoids (labeled by yellow circles and yellow arrows) and the mice ECs derived from hosts (labeled by white circles and white arrowheads) were both detected in the vascular systems in the vOrganoid grafts. Scale bar, 100 μm (left), 10 μm (right). **(F)** Representative immunofluorescence staining figure for GFAP and HUN in the vOrganoid grafts. A few HUN-positive astrocytes were labeled by boxes and magnified in right panels. Scale bar, 50 μm (left), 10 μm (right). **(G)** Representative immunofluorescence staining figure for MBP and HUN to illustrate that myelinization just could be infrequently observed at the border of graft-host commissure. The boxed areas were magnified. Scale bar, 500 μm (left), 100 μm (middle), 50 μm (right). See also S4 Fig. CTIP2, chicken ovalbumin upstream promoter transcription factor (COUP-TF)–interacting protein 2; dpi, days postimplantation; GFAP, glial fibrillary acidic protein; HUN, human nuclear; MBP, myelin basic protein; NOD-SCID, nonobese diabetic severe combined immunodeficient; PSD95, postsynaptic density protein-95; SATB2, SATB homeobox 2; SYB2, synaptobrevin 2; vOrganoid, vascularized organoid.

To test whether synaptic integration emerges in grafted vOrganoids, we performed immunofluorescence staining for SYB2 and PSD95 to observe presynaptic and postsynaptic proteins, respectively, in the graft area close to the graft–host border at 60 dpi. The colocalization and close association of SYB2 and PSD95 indicated that there was synaptic connectivity in the grafts (Fig 4C). However, the presynaptic and postsynaptic sources could not be distinguished in the current study.

Because vOrganoids showed less cell death than nonvascularized organoids in culture, we next asked whether vOrganoid grafts survive better than nonvascularized grafts. We implanted control organoids or vOrganoids into the S1 cortex of NOD-SCID mice and performed immunostaining for cleaved CASPASE 3 in grafts at 60 dpi. Less cell death was observed in the vOrganoid grafts than nonvascularized organoid grafts (S4A and S4B Fig). Additionally, we also compared cell death in organoid grafts with that in in vitro cultured vOrganoids on the same day (day 120). On day 120, there were fewer cleaved CASPASE 3⁺ cells in cultured vOrganoids than control nonvascularized grafts but significantly more in cultured vOrganoids than vOrganoid grafts (S4A and S4B Fig). These results suggest that the vascular systems in vOrganoids can improve cell survival in the host brain.

We next injected Alexa Fluor 594–conjugated dextran into the mouse caudal vein to observe the blood flow in organoid grafts by live two-photon microscopy. Interestingly, steady blood flow was captured in organoid grafts, indicating the formation of a functional vascular system between the graft and host (S3 Movie). The 3D reconstructed images also briefly showed the vascular systems in the grafts (Fig 4D, S4 Movie). In addition, to further demonstrate that the ECs in the grafts had reliably integrated into the new vascular system, immunofluorescence staining for dextran and LAMININ was performed to label blood vessels, while human nuclear (HUN) was used to distinguish vOrganoid grafts from host cells. We observed that human HUVEC-derived HUN⁺ ECs and mouse HUN⁻ ECs coexisted in the blood vessels in vOrganoid grafts 2 months after implantation (Fig 4E).

A study by Mansour and colleagues demonstrated that blood vessels from the host can grow into organoid grafts to support their long-term survival [29]. We next asked whether angiogenesis appears earlier in the vOrganoid grafts than in nonvascularized organoid grafts. Thus, we performed immunostaining for IB4 and HUN in organoid grafts at 30 dpi, a time point at which the blood vessels from the host did not extensively grow into the organoid grafts (S4C Fig). Some IB4⁺ blood vessels were detectable in the center of the vOrganoid grafts, while the majority of blood vessels in the nonvascularized organoid-implanted brains were distributed close to the graft–host borders (S4C Fig).

Considering the supporting roles of glial cells in normal neural activities and the integration of the grafts into host tissue, we next examined the level of gliogenesis within the organoid grafts. Abundant GFAP⁺ astrocytes were present in the graft regions, and some of them were HUN⁺ (Fig 4F). To exclude the possibility that these GFAP⁺ cells might be RGs, we performed coimmunostaining for GFAP and SOX2, as well as for GFAP and paired box 6 (PAX6) (S4D Fig). The results showed that very few GFAP⁺ cells coexpressed SOX2 or PAX6 (S4D Fig), suggesting that the majority of GFAP⁺ cells in the grafts were astrocytes, some of which were native vOrganoid cells (HUN⁺ cells). Furthermore, we also detected signs of myelination in the grafts upon staining for myelin basic protein (MBP). However, consistent with the observation that very few oligodendrocytes were found in cultured vOrganoids by scRNA-seq, only sparse MPB⁺ signals were observed at the implantation border of the grafts, and no myelination was detected in the core regions (Fig 4G), which is consistent with previous studies [29]. These results suggested that the myelinated fibers in the organoid grafts were primarily derived from the host brain and merely intruded into regions of the implantation border and that barely any came from the organoids in the early stage after implantation.

Discussion

The neurovasculature, which is the circulatory system in the brain, is a key component of the NSC microenvironment, which provides oxygen and nutrient support to the brain while removing waste metabolites. Proper development and functioning of the CNS relies on mutual cross talk between the nervous and vascular systems [21,24,58]. Brain organoids are promising models for investigating the development of the human brain and the pathomechanism of mental disorders. However, in current culture systems, the ability of oxygen and nutrients to reach the center of organoids is hampered due to impairments in the circulatory system; therefore, cellular necrosis occurs in the center of organoids. This cellular necrosis in organoids, in turn, heavily limits the continuous growth and long-term maintenance of functional cells in organoids. Many studies have tried to generate vOrganoids by adopting various methods. For example, Cakir and colleagues reported a method for engineering human brain organoids with a functional vascular-like system by introducing hESCs ectopically expressing ETV2 into human cerebral organoids[28]. Here, we have established a reproducible system for the generation of vascularized cerebral vOrganoids by coculturing hESCs/hiPSCs with HUVECs, with minimal introduction of extrinsic signals. HUVECs, which are derived from the endothelium of veins from the umbilical cord, have been used extensively to characterize angiogenesis [59,60]. However, HUVECs are different from HBMECs, which are the main ECs in the human brain [39]. Interestingly, we found that coculture with organoids can induce the development of HUVECs towards brain-like ECs to some extent, as indicated by P-gp expression.

In this system, the ECs connected to form a mesh-like and tube-like vascular structure in vOrganoids. In the early culture stage, the vascular structures preferred to be adjacent to the neural progenitors and were located above the VZ/SVZ region. With rapid neurogenesis, the migrating zone and CP expanded while the VZ/SVZ area shrunk. During this process, the vascular structures gradually emerged in the migrating zone and CP in vOrganoids. ECs have been suggested to secrete soluble factors such as vascular endothelial growth factors (VEGFs), angiopoietin-1 (Ang1), and angiopoietin-2 (Ang2), which promote the self-renewal and differentiation of VZ/SVZ progenitors [49,51,52]. Additionally, the VZ/SVZ is more densely vascularized than its neighboring brain regions during development [50]. Several studies have also indicated that neural cells in neighboring areas can participate in feedback mechanisms to regulate the growth and properties of cells in the vasculature [21]. Therefore, our vOrganoid system to a certain extent recapitulates the in vivo interaction between vascular cells and NSCs/progenitors during neurogenesis. In vOrganoids, ECs may secrete essential extrinsic signals that facilitate neurogenesis. The observations of lower hypoxia signals and fewer cleaved CASPASE 3⁺ cells in vOrganoids than nonvascularized organoids indicate that the vascular systems in vOrganoids may supply even greater levels of oxygen and nutrients for neural progenitors and neurons, although no real blood cells are present in the vascular structure. These factors may promote cell proliferation and differentiation and prevent cell death, which could account for the larger size of and enhanced neurogenesis in vOrganoids. Given the limitations of traditional organoid culture, our vascularized 3D cerebral culture may solve the problem of insufficient oxygen supply and nutrient support to organoids to some extent, thus permitting better growth and functional development of vOrganoids.

vOrganoids mimic cortical development in vivo, and the major cell types in these organoids are RGs, oRGs, IPCs, excitatory neurons, interneurons, astrocytes, and microglia, as detected by both immunostaining and scRNA-seq. In addition, the cell types in cultured vOrganoids and control organoids were both highly similar to those in the human telencephalon at the single-cell transcriptome level [43,61], indicating that vOrganoids could be a potential model for exploring the fundamental questions related to human brain development and neurological diseases. Unfortunately, we did not find clustered ECs in vOrganoids, but this may have been because the dissociation method we used was too mild to break the tight junctions between ECs [62,63]. However, the DEGs between vOrganoids and nonvascularized organoids were enriched in the GO terms of blood vessel morphogenesis, suggesting that there may have been some ECs that were not clustered due to limited cell number caught by scRNA-seq.

Pyramidal excitatory neurons and interneurons in vOrganoids showed an organization that was similar to that observed in the human fetal neocortex. With this classical cytoarchitecture, the neurons gradually matured and formed synaptic connections. We also observed a transition from NMDA receptor–to AMPA receptor–mediated transmission of excitatory synapses in our culture system, indicating that the neurons exhibited a maturation process that contributes to the formation of functional circuits [56]. Together, the results suggest that our vOrganoids derived from coculturing hESCs/hiPSCs with ECs recapitulate human cortical development not only in cell type and cellular organization but also in circuit formation.

A variety of 3D organoid systems have been transplanted in vivo [4,64], and in some cases, they have been used to repair and rescue tissue damage [65], indicating that organoids have the potential to be good resources for cell therapy. Mansour and colleagues proved that the intracerebral implantation of hiPSC-derived brain organoids into immunodeficient mice can develop into a functional vasculature system that significantly rescued the cell death in the grafts and improve the long-term survival of organoid grafts [29]. In their study, there were almost no TUNEL-positive cells detected in the organoid grafts at 50 dpi and 233 dpi. However, we observed about 10% of cleaved CASPASE 3 cells in the vOrganoid grafts. The differences in the culture and transplantation methods and transplantation location might account for the discrepancy. However, the results from both studies suggest that the growth of blood vessels into the grafts help cell survival. In addition, Cakir and colleagues verified that the vascularized human cortical organoids established in their studies can form a functional vasculature system in vivo by implanting vOrganoids subcutaneously into the hind limbs of immune-deficient mice [28]. However, no reports have demonstrated whether the vascular systems in vOrganoids can connect to the host cerebrovascular systems to form a new functional circulation system when implanted in vivo. In our studies, we explored this question by transplanting vOrganoids into the S1 cortex of NOD-SCID mice. In the blood vessels that were located in the vOrganoid graft regions, both human ECs and mouse endothelial cells were detected. Furthermore, a notable level of blood flow was observed in the vOrganoid grafts in mice by two-photon fluorescence imaging. Therefore, our results illustrate that the vascular system in vOrganoids can recruit host ECs to reconstruct a functional vascular system and enable blood flow into the grafts after implantation. Vascularization is a potential vital factor for the survival of organoids, as it may not only promote cell growth in vitro but also play a role in reconstructing blood vessels after transplantation in vivo. Hence, we speculate that our vascularized culture system may be widely applicable for future 3D organoid transplantation in vivo to improve survival rates and functional reconstruction.

Materials and methods

Ethics statement

The animal housing conditions and all experimental procedures in this study were in compliance with the guidelines of the Institutional Animal Care and Use Committee (IACUC) of the Institute of Biophysics, Chinese Academy of Sciences (SYXK2017-22). The human brain tissue collection and research protocols were approved by the Reproductive Study Ethics Committee of Beijing Anzhen Hospital (2014012x) and the Institute of Biophysics (H-W-20131104). The written informed consent was designed as recommended by the ISSCR (International Society for Stem Cell Research) guidelines for fetal tissue donation. The fetal tissue samples were collected after the donor patients signed informed consent documents, which is in strict observance of the legal and institutional ethical regulations from elective pregnancy termination specimens at Beijing Anzhen Hospital, Capital Medical University. All the protocols are in compliance with the "Interim Measures for the Administration of Human Genetic Resources," administered by the Ministry of Science and Technology of China.

Mice

NOD-SCID–immunodeficient mice were purchased from Charles River Laboratories in China (Vital River, Beijing, China) and used for experiments of organoid implantations. All mice were housed in SPF environments with a 12-hour light–dark schedule and had free access to food and water. All the subjects were not involved in any previous procedures.

Tissue sample collection

Fetal brains were collected in ice-cold artificial CSF containing 125.0 mM NaCl, 26.0 mM NaHCO3, 2.5 mM KCl, 2.0 mM CaCl2, 1.0 mM MgCl2, and 1.25 mM NaH2PO4 at a pH of 7.4 when oxygenated (95% O2 and 5% CO2). Gestational age was measured in weeks from the first day of the woman's last menstrual cycle to the sample collecting date.

Three-dimensional vOrganoid culture and differentiation procedure

hESCs (H9 and H3 lines, from ATCC) and iPSCs (AE and LMZ) were maintained on Matrigel-coated 6-well plates (Corning, Corning, NY) and were cultured with Essential 8 Medium (Gibco). On day 0, the hESCs and iPSCs colonies were pretreated for one hour with 20 μM Y27632 (Tocris Bioscience, Bristol, Avon, UK) and were dissociated into single cells by Accutase (STEMCELL Technologies, Vancouver, British Columbia, Canada). HUVECs were cultured in endothelial Cell Growth Medium and dissociated into single cells by TrpLE. The mixture of approximately 3 × 10⁶ dissociated hESCs and 3 × 10⁵ HUVECs was resuspended in Knockout Serum Replacement (KSR) medium (Gibco, Waltham, MA) and plated into 96-well U-shaped polystyrene plates (Thermo Fisher, Waltham, MA). The size of embryonic bodies (EBs) is determined by the number of cells seeding into each well of the plate. The KSR medium was prepared as follows: DMEM/F12 (Gibco, Waltham, MA) was supplemented with 20% KSR (Gibco, Waltham, MA), 2 mM Glutamax (Gibco, Waltham, MA), 0.1 mM nonessential amino acids (NEAA; Gibco, Waltham, MA), 0.1 mM beta-mercaptoethanol (Gibco, Waltham, MA), 3 μM endo-IWR1 (Tocris Bioscience, Bristol, Avon, UK), 0.1 μM LDN-193189 (STEMGENT, Beltsville, MD), and 10 μM SB431542 (Tocris Bioscience, Bristol, Avon, UK). On day 18, the self-organized floating EBs were transferred to low-cell-adhesion 6-well plates (Corning Corning, NY) and further cultured in the neural induction medium containing DMEM/F12, 1:100 N2 supplement (Gibco, Waltham, MA), 2 mM Glutamax (Gibco, Waltham, MA), 0.1 mM NEAA (Gibco, Waltham, MA), 55 μM beta-mercaptoethanol (Gibco, Waltham, MA), and 1 μg/mL heparin. After day 35, the free-floating aggregates were transferred to the neurobasal-type differentiation medium supplemented with 1:50 B27 (Gibco, Waltham, MA), 2 mM Glutamax and 0.1 mM NEAA, 0.55 μM beta-mercaptoethanol, 5 μg/mL heparin, 1% Matrigel, 10 ng/mL BDNF, 10 ng/mL GDNF, and 1 μM cAMP (Sigma-Aldrich, St.Louis, MO). The control nonvascularized organoids were generated with the same workflow, except no HUVECs were added. The vascular and cortical structure analyses have been done in organoids from all the cell lines to test the repeatability of our culture procedure; other experiments in the studies were conducted by the H9 cell line.

Tube formation assay

First, 24-well plates were coated with thawed Matrigel (354230) without introducing air bubbles, and then the plates were plated in a 37°C incubator for at least 30 minutes to allow gelling of the Matrigel. Next, the HUVECs reaching to approximately 80% confluence in a T-25 flask were digested by being incubated in the trypLE solution at 37°C for 3 minutes. After neutralizing the trypLE, 15ml tubes containin HUVECs were centrifuged for 5 minutes at 800g, then the supernatant was removed and the cell pellet suspended in the HUVEC medium, EGM (cc-3124, Lonza, Basel, Switzerland). Adjust the volume with HUVEC medium to have 5 × 10⁵ cells/mL, and plate 200 μL of the cell mixture, which contains 100,000 cells, into each Matrigel-coated well. Then, incubate the 24-well plate overnight at 37°C in a 5% CO2/95% air incubator. The next day, the medium is gently aspirated from each well and is incubated with approximately 500 μL of PFA fixative for 15 minutes. The tube-like structures formed by HUVECs were then immunostained.

Immunofluorescence

Organoids and tissues were fixed by 4% paraformaldehyde in PBS at 4°C for 2 hours and then dehydrated in 30% sucrose in PBS. The fixed and dehydrated organoids and tissues were embedded and frozen at −80°C in O.C.T. compound, sectioned with Leica CM3050S. Cryosections were subjected to antigen retrieval, pretreated (0.3% Triton X-100 in PBS) and incubated for a blocking solution (10% normal donkey serum, 0.1% Triton X-100, and 0.2% gelatin in PBS), followed by incubation with the primary antibodies (SOX2, sc17319, Santa Cruz, Dallas, TX; IB4, 217660-100UG, Millipore, Burlington, MA; LAMININ, ab23753, Abcam, Cambridge, Cambridgeshire, UK; TBR2, ab23345, Abcam, Cambridge, Cambridgeshire, UK; CTIP2, NB100-79809, Novus, Littleton, CO; SATB2, ab34735, Abcam, Cambridge, Cambridgeshire, UK; PAX6, 901301, BioLegend, San Diego, CA; MAP2, ab32454, Abcam, Cambridge, Cambridgeshire, UK; SST, MAB354, Millipore, Burlington, MA; CR, 6B3, Swant, Marly, Fribourg, Switzerland; NeuN, MAB377, Millipore, Burlington, MA; SYB2, 102211, SYSY, Goettingen, Lower Saxony, Germany; PSD95, 124003, SYSY, Goettingen, Lower Saxony, Germany; GFAP, 3670s, CST, Danvers, MA; MBP, ab62631, Abcam, Cambridge, Cambridgeshire, UK; CD31, MAB1393Z, Millipore, Burlington, MA; cleaved CASPASE 3, 9664S, CST, Danvers, MA; BRN2, sc-31983, Santa Cruz, Dallas, TX; GABA, LS-C63358-100, LifeSpan, Seattle, WA; AIF1, LS-B2645-50, LifeSpan, Seattle, WA; FOXP2, ab16046, Abcam, Cambridge, Cambridgeshire, UK; HOPX, sc-30216, Santa Cruz, Dallas, TX; P-gp, MA126528, Pierce, Waltham, MA; RELN, MAB5364, Millipore, Burlington, MA; HUN, ab191181, Abcam, Cambridge, Cambridgeshire, UK;) overnight at 4°C. Immunofluorescence images were acquired with Olympus laser confocal microscope and analyzed with FV10-ASW viewer (Olympus, Tokyo, Japan), ImageJ (NIH), and Photoshop (Adobe).

Electrophysiology

Cultured vOrganoids were embedded in 3% low-melting agarose in artificial cerebral spinal fluid (ACSF; in mM: 126 NaCl, 3 KCl, 26 NaHCO₃, 1.2 NaH₂PO₄, 10 D-glucose, 2.4 CaCl₂, and 1.3 MgCl₂) and sectioned at 200 μm in oxygenated (95% O2 and 5% CO2) ice-cold ACSF with a vibratome (VT1200s, Leica, Wetzlar, Hesse, Germany). The slices were then cultured in a 24-well plate filled with 250 μL/well of neural differentiation medium in an incubator (5% CO₂, 37°C). After a recovery period of at least 24 hours, an individual slice was transferred to a recording chamber and continuously superfused with oxygenated ACSF at a rate of 3–5 mL per minute at 30 ± 1°C. Whole-cell patch clamp recording was performed on cells of vOrganoid slices. Patch pipettes had a 5–7 MΩ resistance when filled with intracellular solution (in mM: 130 potassium gluconate, 16 KCl, 2 MgCl₂, 10 HEPES, 0.2 EGTA, 4 Na₂-ATP, 0.4 Na₃-GTP, 0.1% Lucifer Yellow, and 0.5% neurobiotin, pH = 7.25, adjusted with KOH). Evoked action potentials were recorded in current-clamp mode using a series of injected currents from −60 pA to 280 pA in increments of 20 pA. Whole-cell currents were recorded in voltage-clamp mode with a basal holding potential of −60 mV followed by stimulating pulses from −80 mV to 60 mV with a step size of 10 mV. The membrane potential was held at −70/0 mV when spontaneous EPSCs/IPSCs were recorded. Dual-patch recording was performed in current-clamp mode. A pair of pulses (1 nA, 2-ms duration, 50-ms interval) were injected into each cell separately. The cells were monitored with a 40× Olympus water-immersion objective lens, a microscope (Olympus, BX51 WI) configured for dodt gradient contrast (DGC), and a camera (Andor, iXon3, Belfast, County antrim, UK). Stimulus delivery and data acquisition were conducted with a multiclamp 700B amplifier and a Digidata 1440A (Molecular Devices, San Jose, CA), which were controlled by Clampex 10. The slices were fixed after patch clamp recording. Staining with fluorescein streptavidin (SA-5001, 1:500, Vector, Burlingame, CA) or Texas Red streptavidin (SA-5006, 1:500, Vector, Burlingame, CA) was performed to visualize the morphology of cells.

Calcium imaging

Three microliters of dye solution that contained 50 μg Fluo-4 AM (Life Technologies), 50 μL DMSO, and 200 μg Pluronic F-127 (Sigma) was applied to the surface of each individual slice. After incubation for 30 minutes at 37°C, the slice was transferred to a recording chamber and continuously superfused with oxygenated ACSF (in mM: 126 NaCl, 3 KCl, 26 NaHCO3, 1.2 NaH2PO4, 10 D-glucose, 2.4 CaCl2, and 1.3 MgCl2) at a rate of 3–5 mL per minute at 30 ± 1°C. The slices were washed 30 minutes before imaging. Calcium imaging was acquired at 5 Hz using a camera (Andor iXon3) with a FITC filter set (Ex: 475/35 nm, Em: 530/43 nm) on a BX51WI microscope (Olympus). Data analysis was performed with ImageJ. The ROIs were selected manually, and the mean fluorescence (F) was calculated for each frame. The fluorescence changes over time was calculated as follows: ΔF = (F − Fbasal)/Fbackground, in which Fbasal was the lowest mean fluorescence value during imaging, and Fbackground was the average mean fluorescence across all frames. Since 10 minutes before imaging, TTX (1 μM), CNQX (20 μM), APV (100 μM), and BMI (20 μM) were added by bath application. The slices were rinsed for 30 minutes with ACSF after drug treatments. Different from other drugs, glutamate (100 μM) was added by bath application during imaging.

Implantation of cerebral organoid into mice S1 cortex

Before implantation, cerebral organoids had been cultured for 60 days, and strict screening was performed by bright field (BF) microscopy to select the organoids with the appropriate size and displayed without massive cyst formation. Immune-deficient NOD-SCID mice, aged 8 weeks, were used in our studies. Mice were anesthetized by intraperitoneal injection of avertin. The heads of animals were fixed in a stereotactic frame. The fur above the skull was removed and skin was cut. An approximate 3-mm diameter craniotomy was performed by polishing the skull; the underlying dura mater was removed and a cavity was made by aspiration with a blunt-tip needle attached to a vacuum line. The aspirative lesion was made unilaterally in the region of the S1cortex. Sterile ACSF was used to irrigate the lesion and keep it free of blood throughout the surgery, and a piece of Gelfoam (Pfizer, New York, NY) was used to slow the bleeding and absorb the excess blood. Molten 3% low-melting agarose was dropped in the implantation regions to immobilize the organoid grafts as agarose congealed quickly. Adhesive glue was used to seal the border of implanted organoid grafts. The wound was closed with sutures. Following completion of the surgery, penicillin streptomycin combination was administrated for inflammation and analgesic relief. The mice were then returned into home cages to recover.

Two-photon imaging

For imaging of blood flow in organoid grafts, mice were tail intravenously injected FITC-dextran. The mouse was fixed on the recording setup, with an isoflurane-oxygen mixture of 0.5%–1% (v/v). The in vivo imaging of blood flow was done with a 2-photon laser scanning microscope. The recording chamber was perfused with normal ACSF containing 126 mM NaCl, 3 mM KCl, 1.2 mM NaH₂PO₄, 2.4 mM CaCl₂, 1.3 mM MgCl₂, 26 mM NaHCO₃, and 10 mM D-glucose (pH 7.4 when bubbled with 95% oxygen and 5% CO₂). The temperature of the mouse was kept at approximately 37°C throughout the experiment.

Single-cell dissociation, and library construction

The organoids with and without HUVECs at 65 days and 100 days, respectively, were cut into small pieces and dissociated into single-cell suspensions by using a papain-based dissociation protocol (hibernate E medium with 1 mg/mL papain [Sigma, St.Louis, MO] at 37°C on a thermo cycler at 500g for 15–20 minutes). Single cells were suspended in 0.04% BSA/PBS at the proper concentration to generate cDNA libraries with Single Cell 3′ Reagent Kits, according to the manufacturer’s protocol. Briefly, after the cDNA amplification, enzymatic fragmentation and size selection were performed to optimize the cDNA size. P5, P7, an index sample, and R2 (read 2 primer sequence) were added to each selected cDNA during end repair and adaptor ligation. P5 and P7 primers were used in Illumina bridge amplification of the cDNA (http://10xgenomics.com). Finally, the library was processed on the Illumina platform for sequencing with 150-bp paired-end reads.

Single-cell RNA-seq data preprocessing

Raw sequencing data were processed using Cell Ranger analysis pipeline 2.1.1 with default parameters. Reads were aligned to human reference genome (GRCh38). Cell Ranger output “filtered gene-barcoded” count matrix was loaded into Seurat 3.1.0 [66] for downstream analysis. We excluded poor-quality cells based on the following criterion: nFeature_RNA > 200 or nFeature_RNA < 6,000, mitochondrial gene percentage < 10%. Cells with percentage of hemoglobin reads > 1% (‘HBA1’, ‘HBA2’, ‘HBB’, ‘HBD’, ‘HBE1’, ‘HBG1’, ‘HBG2’, ‘HBM’, ‘HBM’, ‘HBQ1’, ‘HBZ’) were discarded as well. In total, 57,180 cells remained for subsequent analysis. Batch effect correction was performed with function fastMNN from R package batchelor [67] by considering each sample as a batch.

Dimensionality reduction, cell clustering, and cell type identification

We performed principal component analysis (PCA) with Seurat function RunPCA [66] and selected the top 20 statistically significant PCs for clustering by using function FindClusters with resolution parameter set to 2. Known markers SOX2, FAM107A, MKI67, EOMES, DCX, NEUROD2, GAD1, AIF1, AQP4, OLIG1, and RSPO2 were used to name the major cell types RG, oRG, cell cycle, IPC, immature neuron, excitatory neuron, interneuron, microglia, astrocyte, oligodendrocyte and choroid plexus, respectively. UMAP was employed for visualization of our data in 3D coordinates, generated by the RunUMAP [66] function. Three-dimensional UMAP plots were generated using function plot3d from R package rgl.

Identification of DEGs among clusters

Differential gene expression analysis among clusters was performed with Seurat function FindAllMarkers by setting parameter “only pos = TRUE” [66]. Genes with adjusted p-values <0.05 were selected as DEGs.

Ordering cells along pseudo-maturation trajectory and pseudo-time trajectory

To order cells along a pseudo-maturation trajectory, we applied the approach introduced in Petropoulos’s [68] and Mayer’s [69] studies. Following these approaches, we performed dimensionality reduction analysis with Seurat function RunPCA based on the expression of variable genes, followed by fitting a principal curve through the subspace spanned by the first three principal components (PCs). The maturation score for a cell was defined as the arc-length from the beginning of the fitted curve to the points where the cell was fitted on. Then, to assign the curve a starting point, we correlated the PCs with maturation scores and defined the beginning of the curve so that the expression of gene SOX2 is negatively correlated with the maturation score. Once each cell was projected onto the principal curve and given a maturation score, we computed the density of cells along the maturation trajectory for organoids and vOrganoids with R function hist by setting freq = False and fitted curves through them.

Besides a pseudo-maturation score, we also constructed a pseudo-time trajectory with R package monocle3 [44–46]. We first imported the gene expression matrix into monocle, followed by dimensionality reduction analysis with function reduce_dimension, which generated a UMAP graph. We then ran function learn_graph to learn the generated trajectory graph. For ordering cells, we applied the function order_cells by manually selecting the cell cluster that annotated as RG (the cluster that had a higher expression level of the known radial glial marker gene SOX2) as root. After each cell was assigned a pseudo-time value, as described above for maturation trajectory, we computed the density of cells along the pseudo-time trajectory and fitted curves on data.

Mapping organoids cell types to fetal human cortex cell types

To compare cell-type classification between organoid and human cortex datasets, we downloaded count matrix from the previous published work (Nowakowski and colleagues, 2017). Cell types, as assigned to each cell in the previous work, were merged into more general cell types (for example, cells with identity of nIN and IN-CTX were aggregated into a general cell type, Interneuron; EN-PFC and EN-V1 were merged into cell type Excitatory neuron). The Seurat integration approach is committed to identify the homogeneous cell states across different datasets based on dectecting shared sources. Thus, the function of Seurat integration was adopted to integrate the datasets of organoids and human in our studies., and so to combine First, we selected genes for the integrated analysis by function SelectIntegrationFeatures with default parameters. As described in Stuart’s study (Stuart and colleagues, 2019), this function ranked highly variable genes that individually identified in the organoid and fetal human cortex datasets by examining the number of datasets in which they were independently identified as highly variable genes. Next, we identified correspondences among the two datasets using function FindIntegrationAnchors based on the genes selected, as described above [66], and then integrated them into a combined dataset with function IntegrateData, which holds the integrated (or ‘batch-corrected’) gene expression matrix for all cells from the combined dataset. To compute the relations between cell types among organoid and human datasets, we imported the integrated matrix into PAGA and constructed an Anndata data structure followed by running PCA with function sc.tl.pca. Next, we computed the neighborhood graph with function sc.pp.neighbors and constructed the PAGA graph with function sc.tl.paga [70,71]. (the width of edges was scaled with the strength of relations; the size of nodes was scaled with the number of cells of each cell type). To access a general visualization of the distribution of cells, a force-directed graph (ForceAtlas2 layout) of the combined dataset was computed with function sc.tl.draw_graph [70,71].

GO enrichment analysis

GO enrichment analysis was performed with Metascape [72] by importing the DEGs between H9-d65 and HUVEC-d65 cells and visualized via heatmap. Only GO terms with an adjusted p-value <0.05 (Benjamini-Hochberg correction for multiple testing) were considered.

Quantification and statistical analysis

All data were represented as the mean ± SEM. The quantification graphs were made using GraphPad Prism software. The sample size (n) for each analysis can be found in the figure legends.

Data resources

The accession number for the RNA sequencing data reported in this paper is GEO: GSE131094.

Supporting information

S1 Checklist. MDAR checklist.

MDAR, Materials Design Analysis Reporting.

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S1 Fig. The vascular system in vOrganoids promotes cell growth and reduces cell apoptosis.

(A) Representative figure showing the tube formation of HUVECs on matrigel. Scale bar, 200 μm. (B) Representative immunofluorescence staining figure for CD31, IB4, and SOX2 to illustrate that tube-like vascular systems were formed in vOrganoids at 45 days. Scale bar, 50 μm. (C) Representative immunostaining figure for IB4 in the human cortical cryosections at GW12 to show the distribution of blood vessels in the human cortex. Scale bar, 100 μm. (D) Representative BF and immunohistochemical images of vOrganoids derived from hESC-3 and hESC-9 lines. BF images showed on the left and immunohistochemical images for vessel (IB4, green) and progenitor (SOX2, red) showed on the right. Scale bar, 100 μm (left panels), 50 μm (right panels). (E) Representative BF and immunohistochemical images of vOrganoids derived from iPSCs-AE and iPSCs-LMZ cell lines. BF images showed on the left and immunohistochemical images for vessel (IB4, green) and progenitor (SOX2, red) showed on the right. Scale bar, 100 μm (left panels), 50 μm (right panels). (F) Representative immunofluorescence staining figure for cleaved CASPASE 3, IB4 (upper) and HIF1α, IB4 (lower) in the control nonvascularized organoids and vOrganoids at d115. Scale bar, 500 μm. (G) Quantification of the percentages of cleaved CASPASE 3⁺ cells (left) and HIF1α⁺ cells (right) within all cells (DAPI⁺) in the control organoids and vOrganoids at d115, respectively. For cleaved CASPASE 3, n = 5, 5 slices of the control organoids and vOrganoids from three independent experiments. For HIF1α, n = 5, 5 slices of control and vOrganoids in three independent experiments. Data are represented as mean ± SEM, independent samples t test, ***p < 0.001. (H) The diameters of organoids and vOrganoids generated from H9 at day 7, day 31, day 52, day 70 and day 98, respectively. n = 11, 11, 11, 11, 11 for day 7, day 31, day 52, d 70, and day 98, respectively. Data are represented as mean ± SEM, two-way ANOVA analysis, ***p < 0.001. (I) Representative images showing the distribution of PAX6⁺ progenitors in the organoids with or without HUVECs (IB4, red). Scale bar, 50 μm. (J-K) Quantification of the percentages of PAX6⁺ cell within all cells (DAPI⁺) in VZ/SVZ (J) and of the thickness of PAX6⁺ region (K) in control organoids and vOrganoids, respectively. For (J), n = 3, 3 slices from control organoids and vOrganoids in three independent experiments, respectively. For (K), n = 4, 5 slices from control organoids and vOrganoids in three independent experiments, respectively. Data are represented as mean ± SEM, independent samples t test, *p < 0.05. (L) Representative immunofluorescence staining figure for P-gp and IB4 in the human cortical slices at GW12. Scale bar, 100 um. (M) Representative immunofluorescence staining figure for P-gp and IB4 in the tube-like structure formed by HUVECs. Scale bar, 100 um. (N) Representative immunofluorescence staining figure for P-gp and IB4 in the vOrganoids at d83. The signals of P-gp were colocalized with IB4 to a great degree. Scale bar, 200 μm. (O) Representative immunofluorescence staining figure for SATB2 and FOXP2 in the human fetal cortex at GW23 to show the human cortical lamination. Scale bar, 50 μm. (P) Cryosections of vOrganoids were immunostained for the progenitor (PAX6) and layer-specific cortical neuron marker (SATB2) at 65 days. Scale bar, 50 μm. Representative figure was showed. (Q) Cryosections of vOrganoids were immunostained for the layer-specific cortical neuron markers, RELN and TBR1, at 65 days. Scale bar, 100 μm. Representative figure was showed. The numerical data underlying this figure can be found in the S1G, S1H, S1J, S1K Fig sheets of S1 Data. BF, bright field; CD31, platelet and endothelial cell adhesion molecule 1; FOXP2, forkhead box P2; GW, gestational week; hESC, human embryonic stem cell; HIF1α, hypoxia induciable factor 1 subunit alpha; HUVEC, human umbilical vein endothelial cell; IB4, isolectin I-B4; iPSC, induced pluripotent stem cell; P-gp, P-glycoprotein; PAX6, paired box 6; RELN, reelin; SATB2, SATB homeobox 2; SOX2, SRY-box transcription factor 2; TBR1, T-box brain transcription factor 1; vOrganoid, vascularized organoid; VZ/SVZ, ventricular zone/subventricular zone.

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S2 Fig. scRNA-seq of organoids with and without HUVECs.

(A) The cell distributions of each sample of control organoid and vOrganoid were showed in the UMAP plots. As for the control organoids and vOrganoids at each time point, three independent batches of experiments were performed. And in total, 12 samples were included in the studies. Each sample was colored differently in the UMAP plot. (B) Quality control for samples: each dot represents a single cell. Cells with mitochondrial gene percentage >10% (left panel), as well as gene number per cell (nGene) <200 and >6,000 (right panel), were discard in the following analysis. (C) The expression of known gene markers was visualized by UMAP plots and was colored by the expression level (red, high; gray, low). (D) Heatmap showing the expression of DEGs across clusters. Some canonical marker genes were labeled. (E) The transcriptomic correlations between the cell types of organoids and vOrganoid were visualized via heatmap (correlation coefficient: yellow, high; purple, low). (F) The expression of the well-known gene markers in different cell types is showed in the PAGA plots. AQP4, DCX, SOX2, RSPO2, FAM107A, and MKI67 are the specific genes for astrocytes, immature neurons, RG/oRG, choroid plexus, oRG, and cell cycle active cells, respectively. Nodes are colored according to the gene expression levels (light pink, low; dark red, high). (G-H) After being integrated, the cell distributions of organoids (G) and human fetal telencephalon (H) were visualized in a forced-directed graph separately. Each dot represents a single cell and is colored according to the cell types. The width of edges is scaled with the cell–cell connectivity. (I-J) After being integrated, the cell distributions of vOrganoids (I) and human fetal telencephalon (J) were visualized in a forced-directed graph separately. Each dot represents a single cell and is colored according to the cell types. The width of edges is scaled with the cell–cell connectivity. (K-L) The correlations between the cell types of organoids and human fetal telencephalon (K) as well as those between the cell types of vOrganoids and human fetal telencephalon (L) are displayed in the PAGA graph. The cell types in the organoids and human fetal cortex datasets were denoted by the solid and hollow dots, respectively. And the same cell types in two datasets were colored identically. The size of dots was scaled with the cell numbers; width of edges was scaled with the connectivity between cell types. (M-N) The transcriptomic correlations between the cell types of control organoids (M) or vOrganoids (N) and human fetal telencephalon were visualized via heatmap (correlation coefficient: red, high; blue, low). (O) The composition of cell types in the control organoids and vOrganoids at day 65 was illustrated in the bar graph. The numerical as well as metadata underlying this figure can be found in the S2A, S2B, S2C, S2D, S2E, S2G, S2H, S2I, S2J, S2M and S2N Fig sheets of S1 Data. Ast, astrocyte; cell cycle, cell cycle active cell; Ch, choroid plexus; DEG, differentially expressed gene; Endo, endothelial cell; ExN, excitatory neuron; HUVEC, human umbilical vein endothelial cell; ImN, immature neuron; IN, interneuron; IPC, intermediate progenitor cell; MGE, medial ganglionic eminence; MGE div, MGE dividing cell; Mic, microglia; Mural, mural cell; OPC, oligodendrocytes progenitor cell; oRG, outer radial glia; PAGA, partition-based graph abstraction; RG, radial glia cell; scRNA-seq, single-cell RNA sequencing; UMAP, Uniform Mainfold Approximation and Projection; vOrganoid, vascularized organoid.

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S3 Fig. Functional circuits were built in vOrganoids progressively.

(A) Diameters of somata of recorded cells from control organoids and vOrganoids at day 60, day 80, and day 90. Open circles indicate data from individual cells. Filled circles indicate the mean value. Data are represented as mean ± SEM, p = 0.6026, 0.3494, and 0.7491 for day 60, day 80, and day 90, two-sample t test, *p < 0.05, **p < 0.01, ***p < 0.001. (B) Depth of somata of recorded cells from organoids and vOrganoids at day 60, day 80, and day 90. Open circles indicate data from individual cells. Filled circles indicate the mean value. Data are represented as mean ± SEM, p = 0.5799, 0.5248, and 0.8651 for day 60, day 80, and day 90 two-sample t test, *p < 0.05, **p < 0.01, ***p < 0.001. (C) Representative current responses evoked by a series of voltage steps (from −80 mV to +60 mV, in steps of 10 mV) from organoid (upper) and vOrganoid (lower) cells at day 60, day 80, and day 90. (D) Representative evoked action potentials of cell from organoid and vOrganoid at day 90. The amplitudes of injected currents changed from −60 pA to 280 pA in steps of 20 pA. (E) The percentage of firing cells under current stimulations with different amplitudes. The insertion indicates the evoked action potential of cells from organoids (black) and vOrganoids (red). The scale bars indicate 5 ms and 20 mV. The arrow indicates −20 mV. p = 0.0602, 0.0000025, and 0.00012 for day 60, day 80, and day 90. Data are represented as mean ± SEM, paired-sample t test, *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. (F) Resting membrane potentials of recorded cells from organoids and vOrganoids at day 60, day 80, and day 90. Open circles indicate data from individual cells. Filled circles indicate the mean value. Data are represented as mean ± SEM, p = 0.9842, 0.00059, and 0.4102 for day 60, day 80, and day 90, two-sample t test, *p < 0.05, **p < 0.01, ***p < 0.001. (G) Capacitance of recorded cells from organoids and vOrganoids at day 60, day 80, and day 90. Open circles indicate data from individual cells. Filled circles indicate the mean value. Data are represented as mean ± SEM. p = 0.3059, 0.0424, and 0.0075 for day 60, day 80, and day 90, two-sample t test, *p < 0.05, **p < 0.01, ***p < 0.001. (H) An example of spontaneous action potentials recorded from cells of the vOrganoids at day 80. (I) Postsynaptic currents were sensitive to BMI. Representative IPSC event highlighted by a yellow bar displayed at the right panel. (J) Representative staining figure of classical neuron marker NeuN (green) and MAP2 (red) in the vOrganoid of day 210. Scale bar, 100 μm. (K) An example of whole-cell configuration in the vOrganoids of day 210 under DGC. Scale bar, 200 μm. (L) Representative traces of membrane currents elicited by a series of depolarizing pulses (from −80 mV to +60 mV, in steps of 10 mV) from a neuron in the vOrganoid of day 210. (M) Spontaneous EPSCs and IPSCs recorded from the same cells in (L). Yellow bars indicate representative events, which are shown at right. (N-O) Intracellular spontaneous calcium fluctuations were measured before and after the application of 1 μM TTX (N) or 100 μM glutamate (O) in the vOrganoids. Arrows mark the time of addition of glutamate. Scale bar, 100 μm in (N), 50 μm in (O). (P) Injected cells and the cells that coupled with them through gap junctions were visualized by staining of neurobiotin. Scale bar, 20 μm. The numerical data underlying this figure can be found in the S3A, S3B, S3E, S3F, and S3G Fig sheets of S1 Data. BMI, bicuculline methiodide; DGC, dodt gradient contrast; EPSC, excitatory postsynaptic current; IPSC, inhibitory postsynaptic current; MAP2, microtubule associated protein 2; NeuN, RNA binding fox-1 homolog 3; ROI, region of interest; sEPSC, spontaneous excitatory postsynaptic current; sIPSC, spontaneous inhibitory postsynaptic current; TTX, tetrodotoxin; vOrganoid, vascularized organoid.

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S4 Fig. The vascular system formation in vOrganoids grafts.

(A) Representative immunofluorescence staining figure for cleaved CASPASE 3, IB4 in cultured vOrganoids at d120 and for cleaved CASPASE 3, HUN in the control nonvascularized organoid grafts and the vOrganoid grafts at 60 dpi. Scale bar, 50 μm. (B) Quantification of the percentages of cleaved CASPASE 3⁺ cells within all cells (DAPI⁺) in the cultured vOrganoids at d120, nonvascularized and vOrganoid grafts at 60 dpi, respectively. N = 4, 4, 4 samples for the vOrganoids, the nonvascularized organoid grafts, and vOrganoid grafts from three independent experiments, respectively. Data are represented as mean ± SEM, one-way ANOVA, **p < 0.01, ***p < 0.001. The numerical data underlying this figure can be found in the S4B Fig sheet of S1 Data. (C) Representative immunofluorescence staining figure for LAMININ and IB4 in the cryosections of host brains contained the control organoid and vOrganoid grafts at 30 dpi. The immunostaining of LAMININ is individually displayed in the right panels. The boundary between host and graft is outlined by dashed lines. And the arrows point out the healthy-looking blood vessels in the vOrganoid grafts. Scale bar, 100 μm. (D) Representative immunofluorescence staining figure for GFAP/SOX2 and GFAP/PAX6 in the vOrganoid grafts at 60 dpi. Scale bar, 50 μm. CAS3, CASPASE 3; dpi, days postimplantation; GFAP, glial fibrillary acidic protein; HUN, human nuclear; IB4, isolectin I-B4; PAX6, paired box 6; SOX2, SRY-box transcription factor 2; vOrganoid, vascularized organoid.

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S1 Movie. Movie shows the staining of LAMININ (red) and IB4 (green) displayed in 3D, rotating around x-, y-, and z-axes.

IB4, isolectin I-B4.

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S2 Movie. Movie shows the 3D reconstruction of LAMININ-positive vascular structure rotating around the y-axis.

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S3 Movie. Movie shows the functional blood flow in vOrganoids grafts.

vOrganoid, vascularized organoid.

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S4 Movie. Movie shows the 3D reconstruction of dextran-positive blood vessels in vOrganoids grafts.

vOrganoid, vascularized organoid.

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S1 Table. Samples and genes related to scRNA-seq data.

The spreadsheets include the sample information of scRNA-seq, DEGs of major cell types of organoids, and GO terms of the DEGs between progenitor cells. DEG, differentially expressed gene; GO, Gene Ontology; scRNA-seq, single-cell RNA sequencing.

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S1 Data. The numerical data used in all figures are included in S1 Data.

Excel spreadsheet containing, in separate sheets, the underlying numerical data and statistical analysis for figure panels 1M, 2A, 2B, 2C, 2I, 3A, 3B, 3D, 3F, 3I, S1G, S1H, S1J, S1K, S2A, S2B, S2C, S2D, S2E, S2G, S2H, S2I, S2J, S2M, S2N, S3A, S3B, S3E, S3F, S3G, and S4B.

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Acknowledgments

The authors thank Junying Jia for the technical support of FACS and Junjing Zhang for management of laboratory animals. We thank all the members of the Wang lab for discussion and technical assistance.

Abbreviations

ACSF: artificial cerebral spinal fluid
AIF1: allograft inflammatory factor 1
AMPA: α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid
Ang1: angiopoietin-1
APV: DL-2-Amino-5-phosphonopentanoic acid
BBB: blood–brain barrier
BF: bright field
BMI: bicuculline methiodide
BRN2: POU class 3 homeobox 2
CMV: cytomegalovirus
CNQX: 6-Cyano-7-nitroquinoxaline-2,3-dione
CNS: central nervous system
CP: cortical plate
CR: calretinin
CSF: cerebrospinal fluid
CTIP2: chicken ovalbumin upstream promoter transcription factor (COUP-TF)–interacting protein 2
DEG: differentially expressed gene
DGC: dodt gradient contrast
DLX1: distal-less homeobox 1
dpi: days postimplantation
EB: embryonic body
EC: endothelial cell
EOMES: eomesodermin
ExN: excitatory neuron
GABAA: gamma-aminobutyric acid A
GAD1: glutamate decarboxylase 1
GFAP: glial fibrillary acidic protein
GFP: green fluorescent protein
GO: Gene Ontology
GW: gestational week
HBMEC: human brain microvascular endothelial cell
hESC: human embryonic stem cell
HIF1α: hypoxia induciable factor 1 subunit alpha
hiPSC: human-induced pluripotent stem cell
HOPX: homeodomain only protein X
HUN: human nuclear
HUVEC: human umbilical vein endothelial cell
IB4: isolectin I-B4
ImN: immature neuron
IPC: intermediate progenitor cell
iPSC: induced pluripotent stem cell
KCC2: potassium-chloride transporter member 5
KSR: Knockout Serum Replacement
LHX6: LIM homeobox 6
MAP2: microtubule associated protein 2
MBP: myelin basic protein
MGE: medial ganglionic eminence
MGE-div: MGE dividing cell
Mural: mural cells
NEAA: nonessential amino acids
NeuN: RNA binding fox-1 homolog 3
NEUROD2: neuronal differentiation 2
NKX2-1: NK2 homeobox 1
NMDA: N-methyl-D-aspartate
NOD-SCID: nonobese diabetic severe combined immunodeficient
NSC: neural stem cell
OPC: oligodendrocyte progenitor cell
oRG: outer radial glia
P-gp: P-glycoprotein
PAGA: partition-based graph abstraction
PAX6: paired box 6
PC: principal component
PCA: principal component analysis
PSD95: postsynaptic density protein-95
RELN: reelin
RG: radial glia
SATB2: SATB homeobox 2
scRNA-seq: single-cell RNA sequencing
sEPSC: spontaneous excitatory postsynaptic current
sIPSC: spontaneous inhibitory postsynaptic current
SOX2: SRY-box transcription factor 2
SST: somatostatin
SYB2: synaptobrevin 2
TBR2: eomesodermin
TTX: tetrodotoxin
UMAP: Uniform Mainfold Approximation and Projection
VEGF: vascular endothelial growth factor
vOrganoid: vascularized organoid
vRG: ventricular radial glia
VZ/SVZ: ventricular zone/subventricular zone

Data Availability

All relevant data are within the paper and its Supporting Information files.

Funding Statement

This work was supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA16020601, XDB32010100) to XW, National Basic Research Program of China (2019YFA0110101 and 2017YFA0103303 to XW; 2017YFA0102601 to QW), the National Natural Science Foundation of China (31671072 to QW; 31771140 and 81891001 to XW), and the Grants of Beijing Brain Initiative of Beijing Municipal Science & Technology Commission (Z181100001518004) to XW. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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PLoS Biol. doi: 10.1371/journal.pbio.3000705.r001

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13 Jul 2019

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9 Aug 2019

Dear Dr Wang,

Thank you very much for submitting your manuscript "Vascularized human cortical organoids model cortical development in vivo" for consideration as a Methods and Resources at PLOS Biology. Your manuscript has been evaluated by the PLOS Biology editors, an Academic Editor with relevant expertise, and by three independent reviewers.

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Sincerely,

Di Jiang

PLOS Biology

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Reviewer remarks:

Reviewer #1: In this study by Shi et al, the authors generate vascularized cerebral organoids (vOrganoids) from human embryonic stem cells mixed with human endothelial cells in vitro. These vOrganoids display the appropriate neural and endothelial cell markers, structural organization, and functionality typically seen in other organoid studies. The authors implant vOrganoids intracerebrally into mouse brain and observe functional connectivity of vOrganoid vessels with the endogenous vasculature indicated by live two-photon imaging of bloodflow and 3-D reconstruction of vessel morphology. Furthermore, the neurons within vOrganoids are able to mature electrophysiologically as shown by patch-clamp electrophysiology and calcium imaging; these data indicate the presence of both excitatory and inhibitory post-synaptic currents as well as gap junction coupling between neurons suggesting the presence of both chemical and electrical synapses in vOrganoids. These data along with the comprehensive single Cell RNA seq data are valuable to other researchers in the organoid field and support the utility of this system. Furthermore, the authors demonstrate that cerebral implantation can support the long-term health and maturation of organoids to better mimic in vivo development. This study is well-designed and rigorous in its evaluation of vOrganoids and their potential for future research. The data provided are in high quality. The study will be of interest to the field of neuroscience and stem cell biology, as well as disease modeling using pluripotent stem cells. Nevertheless, I have the following suggestions may help further improve the study.

1. In the first paragraph on page 7 the authors state “….which may account for the well-developed vascularized organoids with reduced cell death.” Can the authors please provide some evidence? Using TUNEL or caspase staining for example.

2. Do the authors have any evidence of synaptic integration between the grafted vOrganoid and mouse brain? Such as colocalization of synaptic markers or via electrophysiology. I recognize that this will be a time-consuming experiment. If sections are available, some immunohistochemistry with high-resolution confocal imaging analyses could be helpful.

Minor suggestions.

1. “vOrganoid” needs to be defined in the Abstract section.

2. Usages of “GABAA receptor” and “GABAAR” ; “NMDA receptor” and “NMDAR” ; “AMPA receptor” and “AMPAR” should have some consistency.

3. Figure 1 panel I is not bolded like the other panel letters.

4. What is the relevance of the (#) in the top left of Figure 1 panels I, J, K, L? Statistics should be better defined in figure legend.

5. While infrequent, this study does have some grammatical/syntax errors. I recommend that the authors stringently go over the manuscript and give it to others with a strong command of English to fix these errors.

6. On page 4 the authors state “vRG, oRG, and IPC” acronyms without first defining these for the reader

Reviewer #2: Shi et al. present a method to generate vascularized human cortical organoids (vhCOs) by co-culturing human umbilical vein endothelial cells (HUVECs) with human embryonic stem cells (hESCs). They also graft vhCOs into a mouse cortex and demonstrate that the mouse vasculature and human vascular cells join in forming blood vessels. This manuscript complements the existing literature regarding vascularized cerebral organoids and grafting the organoids into the rodent brain, including Pham et al., 2018 and Mansour et al, 2018. While the technique presented in this manuscript may be a viable way to improve on cerebral organoid technologies, the main novelty is the usage of HUVECs instead of stem cell-derived endothelial cells (Pham et al., 2018) and is therefore somewhat limited. In addition, some of the conclusions in the manuscript are somewhat tenous. Firstly, the claim that the vhCOs present an advantage over non-vascularized ones was not substantiated. Secondly, the claim that this method is highly reproducible was not supported by the data. The study is also somewhat lacking in rigor and statistical analysis. The major concerns are as follows:

1) One of the main arguments of the manuscript is that the vascularized organoids provide an advantage over non-vascularized ones. The authors found that vascularized organoids are slightly larger in Fig S1E, but this is not inherently an advantage. Moreover, they claimed that there is a relatively small proportion of Caspase-3 positive apoptotic cells in grafted vhCOs (Fig S4A), but there is no control group for comparison. More importantly the authors did not present data on Caspase-3 or TUNEL staining of ungrafted vhCOs grown in parallel to non-vascularized ones to demonstrate a decrease in cell death that would support their claim of reduced cell death. Also, no markers for hypoxia were included to support the claim of better oxygenation.

2) The authors also claimed that based on single cell RNAseq data, the vhCOs “exhibited microenvironments to promote neurogenesis and neuronal maturation that resembled in vivo processes.” While the scRNAseq showed the presence of neurogenesis and neuronal maturation, it cannot demonstrate the presence of microenvironments or stem cell niches. The authors stated that the presence of microglia and choroid plexus cells in vhCOs provides a more complex microenvironment that contributes to neurogenesis, but this feature is not unique to the vascularized organoids, and they present no data showing that this contributes to neurogenesis.

3) The authors suggest that the vhCOs had higher maturation scores in Fig. 2H-I, but this is not evident from Fig. 2I. Rather, the cells from the vhCO seem to be scattered around and may be more highly represented among the lower maturation scores. No statistical analysis was presented for these data. The authors also referenced Fig. S2E and claimed that the vhCOs are more mature, but this figure does not seem to compare vascular and non-vascularized hCOs.

4) The authors state that the vhCOs are electrophysiologically more mature because they were able to obtain Na+ currents and spontaneous action potentials at 90-100 days in vitro, earlier than in their prior work without endothelial cells. There was no parallel control with non-vascularized organoids, and therefore one cannot conclude that the presence of vasculature speeds functional maturation of neurons without direct batch-to-batch comparison.

5) The claim that this method is highly reproducible was not supported by the data. The authors note that they used 2 different human embryonic stem cell lines, but it is unclear which experiments were done with which cell line. Fig S1D shows both cell lines, but are all the other experiments from a single line? In addition, throughout the manuscript, details on how many times a certain experiment or differentiation were performed were not included. For example, what proportion of the vhCOs successfully exhibited vascular structures? To demonstrate reproducibility, multiple differentiations should be performed from multiple cell lines with consistent results.

6) For scRNAseq, how many organoids were analyzed? The experiment was not set up to examine variability between organoids or between batches of organoids as other published studies have done to look at reproducibility (e.g Velasco et al, Nature, 2019 and Yoon et al., Nature Methods, 2019).

7) For electrophysiology, what was the success rate for patching cells? Of the cells that were successfully patched, what proportion had spontaneous activity and sodium currents?

8) There are a number of concerns with the in vivo grafting experiments. First, how many times were the grafting experiments done? In the few times that the authors state “n=…” it is unclear if the “n” refers to independent experiments or rather 3 samples from 1 experiment. For example, in Fig. 1M, n=3 samples may mean 3 organoids from a single differentiation, rather than 3 independent differentiations. For Fig 3E and 3G, n=6 was for 6 cells, which may be all from the same organoid. Second, the grafted organoid shown in Fig. 4 appears to be outside the parenchyma of the mouse brain, which it deforms from mass effect. Third, the authors claim laminar organization with CTIP2 being deeper and SATB2 being more superficial. This is not readily evident in Fig. 4B, and moreover, there appear to be DAPI+/CTIP2-/SATB2- rosette structures superficial to the demarcated SATB2 cells. If this recapitulated normal laminar organization, the rosette should be deep to the neurons.

9) In the grafting experiment shown in Fig 4E, the authors state that there are GFAP+ cells in the grafts that appear to be derived from the human ES cells. They should discuss the discrepancy on why they find GFAP+ human cells in the grafts, but not in vitro when examined by scRNAseq. Furthermore, the GFAP staining in Fig 4E appears linearly aligned, which would be unusual for parenchymal astrocytes or astrogliosis, and instead may reflect radial glia - other markers for radial glia should be used to exclude this possibility. Also, the authors state that the myelinated fibers from the mouse are intruding into the graft. How can this be distinguished from the graft intruding into the mouse brain?

Other concerns:

10) The authors should discuss their choice of using HUVECs over other endothelial cells, including stem cell-derived endothelial cells, and in particular brain microvascular endothelial cells, which would seem to be a more appropriate choice.

11) In the introduction, the authors should consider citing cortical and cerebral organoid papers from the Sasai, Lancaster/Knoblich, Pasca, Song Labs (instead of or in addition to midbrain and hippocampal organoid papers). Also, the Mansour et al. paper from the Gage lab should be cite earlier in the introduction. The manuscript authors state that there has been no sophisticated vascular structure observed in brain-like organoids, but the Mansour et al. paper showed this.

12) In Fig. 1C, the tube-like structures are not appreciated well, and in Fig. 1D, the TBR2+ layer appears thin. Also, it is unclear why there should be any cells triple-labeled with Tbr2/Sox2/IB4, as IB4 labels the vascular structures, not the intermediate progenitor cells.

13) In Figure 1E, Sox2 and p-VIM will label mitotic ventricular radial glia, and this is not specific to outer radial glia. The authors should use another marker such as HOPX for outer radial glia. Also, this staining was done at d65, an age at which on scRNA seq there were no HOPX+ outer radial glia.

14) Fig 1K-M: Reelin and Cux1 immunolabeling would be helpful to show superficial cortical layer markers.

15) The lack of astrocytes on scRNA is puzzling. This should be confirmed with GFAP staining of the organoids.

16) In Fig. 2B, it appears that there are many more cells in the vOrganoids at d100 and d65 compared to the unvascularized organoids. This may be because the plot has opaque dots for the vOrganoids that are overlayed on top of the dots for the unvascularlized organoids. tSNE plots showing the vOrganoids and unvascularized organoids separately would help visualized these data. This also applies to Fig 2I. In addition, for the gene ontology analysis in Fig. 2F, are there several marker genes that fall under each category? If so, brackets should be used to show which rows of the heatmap correspond to the GO class. If not, having just 1 enriched synaptic gene (SYT1) does not make a compelling argument that vOrganoids are enriched in synaptic markers.

17) Fig 2D: The choice of comparing the organoid scRNAseq data to a dataset containing 2300 cells from human fetal prefrontal cortex from gestational ages (GW8-26) should be explained. The samples are restricted to a specific brain region. The dataset from Nowakowski et al., 2017 may be a better comparison.

18) Fig 2D and S2D: The interneuron populations of the organoids/vOrganoids do not overlap well with the human prefrontal cortex samples on the tSNE plot. The authors should comment on this and determine what genes may be differentially expressed between these two groups. Also, it is not clear if the interneurons derive from ganglionic eminence-like progenitors – markers for these (e.g., NKX2.1, DLX1/2, LHX6) should be examined by immunostaining and scRNAseq.

19) Fig 2H-I: The maturation trajectory does not appear to be tightly correlated compared to the cited study (Mayer et al, 2018).

20) For sodium/membrane current recordings (Fig 3A and S3D), additional steps to other voltages should be included (not just +20 and -20 mV).

21) The authors stated in the discussion “Pyramidal excitatory neurons and interneurons in the vOrganoids were aligned in layers that were similar to those of human neocortical lamination.” This was not demonstrated by the data.

22) Fig S1G: It is unclear what the white and black bars represent, and they are switched in position between the top and bottom panels.

23) In the asbstract, the “C” in sEPSCs and sIPSCs stands for current, not potential.

Reviewer #3: Shi et al develop a cerebral organoid differentiation protocol where they achieve generation of the vasculature (vOrganoids) by co-culturing HUVEC cells with human ESCs differentiated into cerebral organoids.

Overall, the manuscript is poorly prepared. Many descriptions lack proper quantifications, and many quantifications lack proper statistical reporting. There are numerous grammatical errors throughout the manuscript, and the logic of the experiments is difficult to follow.

There are several potentially interesting findings. For example, it is interesting that the vasculature localizes to the SVZ and observing spontaneous action potentials by day 90 suggests the vOrganoids mature well. Similarly, observing microglia in a forebrain protocol is unexpected and potentially useful.

However, my biggest concern that the authors have not really convincingly showed that their method of vOrganoids cultures have any major benefits over existing protocols.

Major concerns,

1) Despite a long introduction, the authors do a very poor job reviewing the state of the field of vascularization in organoids. For example, there is only a brief description of Mansour et al., 2018 in the discussion, and Pham et al., 2018 is only briefly mentioned in the introduction. Moreover Daviaud et al., 2018 is not really described.

2) The main point of the article is the role of endothelial cells, yet there is very little characterization of these cells. These cells seem to have not been captured by the scRNA-seq, but could be characterized by other methods. In particular, HUVEC cells are likely very different from endothelial cells in the brain, but perhaps co-culture induces the HUVEC cells to a more brain like endothelial cell fate. This should be examined, and the authors should clearly acknowledge the differences between these cells and endothelial cells of the brain.

3) Throughout the manuscript, the authors provide insufficient information about many of the methods used for quantifying the phenotypes. Many descriptions appear to reflect some kind of quantification but no quantification or statistics is shown. For example, quantification of organoid growth presented in Figure S1 E – it is completely unclear from the figure description how many individuals were used, how many organoids, how were they selected, what statistical method was used for comparison, was there multiple hypothesis correction, what was the data distribution. This is just one of many examples where reporting on data quantification is unacceptable and makes it impossible for me to evaluate the statistical rigor in this manuscript.

4) In addition, I was expecting extensive characterization of the strengths and weakness of vOrganoids vs. conventional organoids, but the comparisons are limited. In particular, how much is cell death reduced in organoids, and do the vOrganoids survive transplant better than conventional organoids? For example, in In Figure S4 the authors show a Caspase3 stain but nothing to compare it too. Are there many Cas3 positive cells in organoids to begin with? Could they provide some quantification in organoids that were and were not transplanted into mouse? Similarly, is there more blood flow into vOrganoids than conventional organoids after transplant? Could the size increase of vOrganoids be driven by expansion of HUVECs themselves? There are some differentially expressed genes, but these should be validated by immuno and quantification across normal and vOrganoids.

5) At the end of the first results section the authors claim that “higher degree of vasculature assures sufficient oxygen and nutrient support for cell proliferation and differentiation.” However, it is unclear to me how this could possibly be achieved simply after co-culturing HUVECs. If the authors believe that this is the case they should address this experimentally. For example, if the hollow tubing of vasculature supplies more oxygen, this is testable.

6) Description of electrophysiological properties appears to be performed well, but it is unclear what novel observations are made. This component would be strengthened by experiments showing differences between the vOrganoids and standard organoids.

7) Most of the data showing human cerebral organoid cells after transplantation are very premature and mostly show the presence of different cell types that are normally found in an organoid after long enough culture. Integration into the mouse tissue is not novel and has been reported before.

Minor concerns

- Saying that organoids are laminated is quite a stretch. The reality is that there is a clear separation of progenitors vs neurons but within the neuronal layer having “cortical”-like layers has not been perfected. For the point of this article lamination is not relevant so I would recommend removing references to it. Moreover, their definition of upper layer neurons is SATB2+ cells, but this marker labels an identity (callosal neurons of all layers) not a layer. Similarly, CTIP2 labels subcerebral projection neurons.

- The appearance of microglia was reported in one other study (Ornel et al., 2018), but is a bit mysterious. Does this also occur in conventional organoids by this group or is it related to the HUVEC cells? Can the authors explain this result further? How are these distinguished from macrophages? Also, staining for AIF1 in figure 2 seems to be present almost everywhere in the field of view. It is unclear whether the staining was specific to AIF1.

- “The transplantation of cerebral organoids that are derived from hESCs or iPSCs into injured areas may be a promising therapy for improving neurologic deficits that are caused by trauma or neural degeneration”. I do not think there is a need for this sentence in the manuscript. What evidence do they have that transplanting an heterogeneous tissue (vs for instance transplanting pure neuronal subtypes) is preferable.

- Authors might consider a different nomenclature to refer to vascularized organoids. It is only natural to assume that abbreviations refer to regionalized organoids, so vOrganoids make it sound as “ventral” organoids, which is not what they intend.

- The maturation analysis in figure S2 is confusing - choroid should be a separate lineage from excitatory neurons, and not included as a seeming progenitor cell

- In the methods, the co-clustering of scRNA-seq data is poorly explained. For example, what does a union of common highly variable genes mean? Is this the union or the intersection?

PLoS Biol. 2020 May 13;18(5):e3000705. doi: 10.1371/journal.pbio.3000705.r003

Author response to Decision Letter 1

16 Dec 2019

Attachment

Submitted filename: Response to Reviewers.pdf

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PLoS Biol. doi: 10.1371/journal.pbio.3000705.r004

Decision Letter 2

Di Jiang

31 Jan 2020

Dear Dr Wang,

Thank you very much for submitting a revised version of your manuscript "Vascularized human cortical organoids (vOrganoid) model cortical development in vivo" for consideration as a Methods and Resources at PLOS Biology. This revised version of your manuscript has been evaluated by the PLOS Biology editors, the Academic Editor and the original reviewers.

In light of the reviews (below), we are pleased to offer you the opportunity to address the remaining points from the reviewers in a revised version that we anticipate should not take you very long. Our Academic Editor advises that the following points are essential for the publication of the paper, whereas the other concerns not listed below are not required.

1) The issue regarding caspase-3 antibody raised by reviewer 2;

2) Reviewer 2's suggestion on citing the new paper by Cakir et al (2019) and all this reviewer's minor concerns;

3) Reviewer 3's concern on Figure 2K and Table S1 - most part of this reviewer's concern #2;

4) Reviewer 3’s concern #3. Specifically, “clearly state what steps were taken to record from neurons of the same type in an unbiased way because differences could arise from recording from different neuron subtypes between conditions, or even neurons of different size. Is the result of a difference between vOrganoid and control organoids significant, or just a trend, no p-value is provided?“;

5) Part of reviewer 3's concern #4 : “a control experiment of whether induction occurs in HUVECs cultured on their own, and probably a control experiment that the P-glycoprotein antibody labels human HBMECs”;

6) All the minor concerns from reviewer 3.

After re-submission, we will assess your revised manuscript and your response to the reviewers' comments and we may consult the reviewers again. We expect to receive your revised manuscript within 1 month.

Please email us (plosbiology@plos.org) if you have any questions or concerns, or would like to request an extension. At this stage, your manuscript remains formally under active consideration at our journal; please notify us by email if you do not intend to submit a revision so that we may end consideration of the manuscript at PLOS Biology.

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Sincerely,

Di Jiang

PLOS Biology

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REVIEWS:

Reviewer #1: Based on the authors' answers and new supporting information to our previous concerns for the manuscript, we feel that our concerns have been sufficiently addressed and would advise publication of this manuscript. This is paper will enrich the current literature on organoids and presents methodology for more physiological and meaningful study using this system.

Reviewer #2: This revised manuscript by Shi et al. employs human umbilical vein endotheial cells (HUVECs) co-cultured with human embryonic stem cells (hESCs) and human induced pluripotent stem cells (hIPSCs) to generate cerebral organoids. The authors have added substantial experimental data which bolster their findings and address most of the concerns brought up by the reviewers. They show that the vOrganoids have thicker neural progenitor zones, enhanced neurogenesis, and earlier maturation of electrophysiological properties. They also provide evidence supporting the reproducibility of their data by using 2 hESC and 2 hIPSC lines to generate vOrganoids, and they give additional information about the number of replicates and their statistical analyses.

There are several remaining concerns:

1) The authors demonstrate decreased caspase-3 staining in their vOrganoids compared to controls to support less cell death, but they use an antibody recognizing full length, rather than cleaved, caspase-3. Full length caspase-3 may not accurately reflect apoptotic cell death and measurement of cleaved caspase-3 should be used instead.

2) While the single cell RNA-seq data (Figure 2) demonstrate cell type diversity in the vOrganoids, these data do not make a compelling case that the vOrganoids are an improvement over non-vascularized ones. The main differences are that the vOrganoids have increased NEUROD2+ neurons, which may suggest that neurogenesis is promoted. An increase in NEUROD2+ neurons is not necessarily advantageous. The authors also note that there are differentially expressed genes and that on GO analysis there are some enriched pathways, but again this does not show any advantage (e.g. better recapitulation of developing human fetal brain, or improved cell type diversity) with using HUVECs.

3) In the time that the authors revised this manuscript, an additional publication using ETV2-expressing hESCS to generate cerebral organoids with a vascular system was published (Cakir et al, Nature Methods, vol 16, November 2019, 1169-1175). The authors should reference this paper in their introduction and discuss/compare this paper with the present results in the conclusion of this manuscript.

Additional minor concerns:

1) Several abbreviations (e.g. vRG, oRG) remain undefined in the text.

2) The authors responded that they toned down the claims of lamination in the organoids, but in the abstract, they still state that their model recapitulates lamination of the neocortex. This statement should be removed.

3) In lines 100-101, the authors state that "all of these studies indicate that vascularization is important for organoid survival." This is overstated, as there are plenty of protocols that do not have vascularization but have good organoid viability.

4) For Fig S1G, it would be preferable if the data were presented as individual data points with mean/standard deviation rather than a bar graph, to better demonstrate the variability/range of the data.

5) The claim that vOrganoids are larger than controls (Fig. S1H) is questionable. The error bars appear very small compared to what might be expected for typical size variability of organoids--are the error bars standard deviation or standard error of the mean? Which statistical test was performed? It would be appropriate to do 2-way ANOVA with multiple comparisons, rather than do repeated t-tests. Even if the data are statistically significant, the relative difference in size does not appear to be of biological significance.

6) For Fig. S1L, there is no control staining—perhaps the HUVECs express p-gp even in the absence of being cultured with the organoid?

7) The calcium imaging data in Fig 3I was normalized to 1 for both the d50 and d85 conditions. In order to see relative differences between d50 and d85 (one would expect increased activity with older organoids), the data should be normalized to just the day 50 organoid in ACSF.

8) The authors should provide additional explanation regarding the response of calcium transients to pharmacological treatments of the organoids (Fig. 3I and lines 274-281). Why are CNQX and APV more effective at reducing calcium transients at the later time point? The authors should also explain in more detail the effect of BMI. The effect at d50 of decreasing calcium transients may be a developmental effect, where opening of GABA-A receptors can depolarize the cell membrane, since the chloride ion concentration is higher inside the cell compared to outside the cell. The effect at d85 (where there does not seem to be an effect of the BMI), may be the transition point when the intracellular chloride ion concentration is decreasing, and opening of the GABA-A receptors may not have an effect on the membrane potential.

9) Figure S3H and I are discordant with each other. Why do the tracings in the ACSF condition in panel H show calcium transients, but the ACSF in panel I has even less activity than the amount seen in the TTX condition of panel H?

10) For Figure 4C, one cannot conclude that there is synaptic connectivity between the organoid graft and the host brain. The co-localization of pre-synaptic and post-synaptic markers could also be mouse-to-mouse or human-to-human.

Reviewer #3: Manuscript by Shi et al., presents a vascularized organoid model that could potentially serve as an improved system for modeling aspects of cortical brain development, for transplanting organoids into mice, and for treating brain disorders. The revision attempts to more explicitly address whether and in what ways the vOrganoids are an improvement over existing organoid models. The manuscript is improved in this respect. For example, I find the improved grafting of vOrganoids compared with control organoids and the mixing of HUVEC derived and mouse vascular cells particularly interesting. However, I still have major concerns that I address below, in the context of each stated improvement.

1) The study describes "improved cell survival in vOrganoids during culture (new Fig S1F-G) and larger size (new Fig.S1H)"

Figures S1F and S1G are key to showing improvements in vOrganoids and should probably be in the main text. However, understanding the mechanism of these improvements would be particularly powerful, especially since the authors discuss possibilities of nutrients, signaling and oxygen several times. Therefore, it would be really add to the manuscript's impact if the authors could test whether the vasculature increases oxygen tension inside the organoids (thereby influence the HIF1a protein levels, as performed in Pasca 2019.

Also, can the authors rule out that the increased size is not simply driven by the number of HUVECs transplanted and their proliferative potential?

2) The study states scRNA-seq suggests improvement in gene expression and neurogenesis in vOrganoids

I'm particularly concerned about the scRNA-seq data analysis. The interpretation of clustering is useful and very interesting that subcortical cell types emerge. However, these datasets could allow for a quantification of whether vOrganoid cells of particular types more closely resemble fetal cell counterparts than control organoids.

Instead, the study simply implies the vOrganoid cells are improved, but only shows that you can integrate the organoid cells with primary cells using a batch correction algorithm. However, these batch correction algorithms can overcome severe differences between conditions, and it is unclear whether the integration is superior with vOrganoid cells.

Figure 2K could further help address if vOrganoids bring cells closer to fetal cell gene expression if the differential expression between vOrganoids were put in context of fetal cell data.

However, I have major reservations with this analysis and with Table S1. First, it is unclear what cell types are listed in the Fig 2K table. Is there a cell cycle gene expression difference between progenitors across vOrganoid and control conditions, or are there more progenitor cells in the control organoids? A meaningful comparison must analyze cells of the same type, but the heatmap looks like some sort of composition difference between the control and vOrganoid cells analyzed, with more dividing progenitors in the control organoids.

In this regard, the enrichments in Figure 2K and Table S1 are incomplete, unconvincing, and potentially misleading. The enrichments of vOrganoid cells in "axon guidance," "blood vessel morphogenesis" and "cellular response to oxygen levels" sound at first like they represent a more fetal-like state (and a quick read of the manuscript would interpret this analysis as evidence of improvements in vOrganoids, but the genes listed in the table for enrichments are either very few (3 genes in total account for multiple statements about cellular response to oxygen!) or indicative of an artifact (6/7 genes listed for axon guidance are ribosomal protein transcripts that often reflect outlier cells to be removed in scRNA-seq QC!). The p-values for the GO terms also must be corrected for multiple hypothesis testing.

This analysis should be dropped or completely re-done, explicitly addressing how cells of the same type differ across conditions and whether these differences produce more fetal-like cells in vOrganoids.

3) The study describes earlier maturation of the active electrophysiological activities (new Fig 3A-B and Fig.S3A-B);

The study should clearly state what steps were taken to record from neurons of the same type in an unbiased way because differences could arise from recording from different neuron subtypes between conditions, or even neurons of different size. Is the result of a difference between vOrganoid and control organoids significant, or just a trend, no p-value is provided? The other physiological metrics are interesting background, but it must be made very clear that these metrics were not compared to control organoids and that it is therefore unclear whether vascularization influenced these features

4) The study suggests the HUVEC cells change to resemble human brain vasculature, potentially indicating an unappreciated utility for this cell type which also has the advantage of being easy to access

However, the observed induction of P-glycoprotein experiment in HUVECs needs a control experiment of whether induction occurs in HUVECs cultured on their own, and probably a control experiment that the P-glycoprotein antibody lables human HBMECs. The interpretation would also be more believable if a range of HBMEC markers were induced instead of just one.

Minor comments:

-abstract still says "recapitulate lamination of neocortex" but there is no evidence for cortical layers resembling in vivo lamination

-The data in figure panels does not support the text that "later-born superficial layer neurons (SATB2+cells) were more superficially localized to the CTIP2+ neurons" - certainly the SATB2 neurons accumulate superficial to SOX2 and TBR2 but evidence for cortical plate lamination is weak in organoid field beyond some coarse SATB2 CTIP2 stains that lack quantification across replicates, individuals, and developmental time. Even the TBR1 staining in S1O extends to the surface and there is RELN staining very interior. Regardless, without comparing quantitative cortical plate lamination phenotypes in vOrganoids to control organoids, it is impossible to know whether the resolution of layers improves by this treatment.

In addition, while it is true that virtually all upper layer projection neurons are SATB2+, over 30% of deep layer neurons project through the corpus callosum and are SATB2+ (refer to McConell, Chen, Macklis, and Arlotta labs literature). I would encourage the author to either refer to these cells as callosal neurons or use markers with a more clear laminar restriction such as CUX1 and CUX2 (for example Quadrato et al.)

-Figure S1 E show less extensive IB4 staining in iPSC-derived organoids and Figure S1F shows much of the IB4 localization on the surface of older organoids (D115), which differs from the internal staining in Figure 1G (d45, d65). From the discussion, it sounds like the vasculature being precisely in the VZ/SVZ during early culture stages - can the authors clarify how the HUVEC distribution changes over time and how consistent the transition is?

-In Fig 2 - why use both UMAP and PAGA for visualization of dimensionality reduction? Also, explain what PAGA stands for and how it is performed. In Figure 2, explain the method for batch integration and how it was corroborated by other methods.

-What is the physiological significance of increased outward current in vOrganoids and what other properties might be expected to change along with this one?

-it is uncertain whether there is synaptic connectivity between the mouse brain and organoid cells based on these studies, although other reports (Mansour, Vanderhagen, de Paola indicate this occurs)

-It is very interesting that "the vascular systems in the vOrganoids could improve the cell survival in the host" - Fig 4E is exciting, providing evidence for the host vasculature connecting to the HUVECs, which could explain the improvements in transplant of vOrganoids

-This study observes a 40% Caspase3/DAPI staining in grafted organoids that lack HUVEC cells, which seems very high compared to Mansour et al 2018 who observe almost no TUNEL staining in day 50 and day 233 post-impantation organoids - is there an interpretation for this different observation? The Mansour paper makes it sound like grafting a normal organoid already solves the apoptosis problem, but that does not seem to be the case here. Because the improved grafting of vOrganoids may be a key feature, it would be important to address this discrepancy in some way, even just in the text.

-Figure 4B organoid staining does not resemble cortical plate lamination or cortical folding. There are more clusters of SATB2 by the surface, but these do not form a layer, and as acknowledge, these are interrupted by VZ-like rosettes, which would account for the bumpiness described as cortical folding. Strong claims of cortical layer formation and cortical folding require strong evidence, including clear definitions and quantification which are lacking, and it is unhelpful for the field to promote confusion here. Also, it is unclear how these observations compare to control organoids.

PLoS Biol. 2020 May 13;18(5):e3000705. doi: 10.1371/journal.pbio.3000705.r005

Author response to Decision Letter 2

9 Mar 2020

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PLoS Biol. doi: 10.1371/journal.pbio.3000705.r006

Decision Letter 3

Di Jiang

10 Mar 2020

Dear Dr Wang,

Thank you for submitting your revised Methods and Resources entitled "Vascularized human cortical organoids (vOrganoid) model cortical development in vivo" for publication in PLOS Biology. I have now obtained advice from the Academic Editor who has assessed your revision.

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PLoS Biol. 2020 May 13;18(5):e3000705. doi: 10.1371/journal.pbio.3000705.r007

Author response to Decision Letter 3

17 Apr 2020

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PLoS Biol. doi: 10.1371/journal.pbio.3000705.r008

Decision Letter 4

Di Jiang

17 Apr 2020

Dear Dr Wang,

On behalf of my colleagues and the Academic Editor, Bing Ye, I am pleased to inform you that we will be delighted to publish your Methods and Resources in PLOS Biology.

The files will now enter our production system. You will receive a copyedited version of the manuscript, along with your figures for a final review. You will be given two business days to review and approve the copyedit. Then, within a week, you will receive a PDF proof of your typeset article. You will have two days to review the PDF and make any final corrections. If there is a chance that you'll be unavailable during the copy editing/proof review period, please provide us with contact details of one of the other authors whom you nominate to handle these stages on your behalf. This will ensure that any requested corrections reach the production department in time for publication.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Checklist. MDAR checklist.

MDAR, Materials Design Analysis Reporting.

(DOCX)

Click here for additional data file.^{(31.9KB, docx)}

S1 Fig. The vascular system in vOrganoids promotes cell growth and reduces cell apoptosis.

(TIF)

Click here for additional data file.^{(6.4MB, tif)}

S2 Fig. scRNA-seq of organoids with and without HUVECs.

(TIF)

Click here for additional data file.^{(3.2MB, tif)}

S3 Fig. Functional circuits were built in vOrganoids progressively.

(TIF)

Click here for additional data file.^{(2.1MB, tif)}

S4 Fig. The vascular system formation in vOrganoids grafts.

(TIF)

Click here for additional data file.^{(5MB, tif)}

S1 Movie. Movie shows the staining of LAMININ (red) and IB4 (green) displayed in 3D, rotating around x-, y-, and z-axes.

IB4, isolectin I-B4.

(AVI)

Click here for additional data file.^{(8.3MB, avi)}

S2 Movie. Movie shows the 3D reconstruction of LAMININ-positive vascular structure rotating around the y-axis.

(AVI)

Click here for additional data file.^{(3.2MB, avi)}

S3 Movie. Movie shows the functional blood flow in vOrganoids grafts.

vOrganoid, vascularized organoid.

(AVI)

Click here for additional data file.^{(7.4MB, avi)}

S4 Movie. Movie shows the 3D reconstruction of dextran-positive blood vessels in vOrganoids grafts.

vOrganoid, vascularized organoid.

(MOV)

Click here for additional data file.^{(6.5MB, mov)}

S1 Table. Samples and genes related to scRNA-seq data.

(XLSX)

Click here for additional data file.^{(55.4KB, xlsx)}

S1 Data. The numerical data used in all figures are included in S1 Data.

(XLSX)

Click here for additional data file.^{(27.5MB, xlsx)}

Attachment

Submitted filename: Response to Reviewers.pdf

Click here for additional data file.^{(258.1KB, pdf)}

Attachment

Submitted filename: Response to Reviewers 0309_V2.pdf

Click here for additional data file.^{(3.5MB, pdf)}

Attachment

Submitted filename: Response.docx

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Data Availability Statement

All relevant data are within the paper and its Supporting Information files.

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PERMALINK

Vascularized human cortical organoids (vOrganoids) model cortical development in vivo

Yingchao Shi

Le Sun

Mengdi Wang

Jianwei Liu

Suijuan Zhong

Rui Li

Peng Li

Lijie Guo

Ai Fang

Ruiguo Chen

Woo-Ping Ge

Qian Wu

Xiaoqun Wang

Roles

Abstract

Introduction

Results

Vascularization in the 3D vOrganoid culture system

Fig 1. Cerebral vOrganoids with vascular system recapitulate the cortical spatial organization.

Recapture of cell subtypes during neurogenesis

Fig 2. Cell type mapping between the scRNA-seq data of organoids and human fetal telencephalon.

Modeling functionality maturation during neurogenesis

Fig 3. Electrophysiological properties of cells in the vOrganoids at different developmental stages.

Transplantation of vOrganoids reconstructs the vascular system in the mouse cortex

Fig 4. The vOrganoids play important roles in the reconstruction of vascular system after transplantation.

Discussion

Materials and methods

Ethics statement

Mice

Tissue sample collection

Three-dimensional vOrganoid culture and differentiation procedure

Tube formation assay

Immunofluorescence

Electrophysiology

Calcium imaging

Implantation of cerebral organoid into mice S1 cortex

Two-photon imaging

Single-cell dissociation, and library construction

Single-cell RNA-seq data preprocessing

Dimensionality reduction, cell clustering, and cell type identification

Identification of DEGs among clusters

Ordering cells along pseudo-maturation trajectory and pseudo-time trajectory

Mapping organoids cell types to fetal human cortex cell types

GO enrichment analysis

Quantification and statistical analysis

Data resources

Supporting information

Acknowledgments

Abbreviations

Data Availability

Funding Statement

References

Decision Letter 0

Di Jiang

Roles

Decision Letter 1

Di Jiang

Roles

Author response to Decision Letter 1

Decision Letter 2

Di Jiang

Roles

Author response to Decision Letter 2

Decision Letter 3

Di Jiang

Roles

Author response to Decision Letter 3

Decision Letter 4

Di Jiang

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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