Generation of Hi-Q brain organoids
Conventionally, most unguided brain organoid differentiation methods include embedding disassociated hiPSC with or without an extracellular matrix and processing them into the EBs before differentiation into the neurospheres5,6,24,25. We previously demonstrated a method of directly inducing differentiation into neural epithelium from hiPSC. These brain organoids expressed various ranges of cell types, electrically active neural networks, optic vesicles, and cell types derived from surface ectoderm3,26,27. This protocol involved the manual processing of neurospheres. As objects in culture dishes, neurospheres tend to exhibit variable shapes and sizes, and most importantly, it limits the number of organoids one can generate per batch.
We reasoned that differentiating hiPSC directly into neurospheres in a confined space could restrict heterogeneity and generate uniform-sized brain organoids in large quantities with increased homogeneity and similar cell diversity. To do this, we exposed disassociated hiPSC directly to a neural induction medium (Supplementary Table 1) to induce the neurospheres in microwells equipped with a round bottom satisfying two prerequisites. First, microwells allow identical diffusion conditions for all spheres and unique physiological sphere formation. Second, microwell material does not require precoating, which could dampen the cells’ attachment or a centrifugation step, forcing cell pelleting. For this purpose, we fabricated a custom-designed spherical plate using a medical-grade, inert Cyclo-Olefin-Copolymer (COC), which offers an ideal surface property. The plate consists of 24 large wells, which are micropatterned to contain 185 equally sized microwells of 1x1mm at the opening and 180 µm in diameter at their round base (Fig. 1A). Typically, each microwell exhibits an inverted pyramid shape with a rounded bottom. This geometry induces the seeded cells to form spheres through mutual adhesion.
A Microscopic view showing a custom-designed spherical plate with microwells and schematic view of the inverted pyramid-like microwell. The angles and measurements are shown. B hiPSC settles and readily forms spheres in the spherical plate’s microwells. The panel shows the scale bar. C Formation of neurospheres in the microwells of the spherical plate. The magnified image at the right shows a representative neurosphere. Magnified panels show a neural rosette stained with actin (green) with primary cilia emanating into the lumen (L) at the apical side of the rosette marked by Arl13B (Red). Panels show the scale bar. D Different stages of Hi-Q brain organoid generation. E A group of neurospheres. The graph at right shows no significant difference between the organoid diameter across four independent batches. At least twenty (n = 20) randomly chosen neurospheres were measured from each batch. Statistical analysis was done using one-way ANOVA, followed by Tukey’s multiple comparisons test. Data presented as mean ± SEM. The cell line used is IMR90. The panel shows the scale bar. F Maturation of neurospheres into Hi-Q brain organoids in spinner flasks. Macroscopic images show a group of organoids. The panel shows the scale bar. G Hi-Q brain organoids increase in size progressively over time from day 15 to day 150. The panel shows the scale bar. H The average diameter of twenty-day (i) and fifty-day (ii) old organoids were differentiated from four independent hiPSC lines. Note that there is no significant difference among the different hiPSC donors within each time point. At least twenty-five (n = 25) randomly chosen organoids were analyzed across three independent batches (N = 3). Statistical analysis was done using one-way ANOVA, followed by Tukey’s multiple comparisons test. Data presented as mean ± SEM. I The graph shows no size difference between twenty-day and sixty-day-old organoids, showing a regulated growth rate between two-time points. At least twenty-five (n = 25) randomly chosen organoids were analyzed across three independent batches (N = 3). Data distribution is given in the panel (H). Statistical analysis was done using one-way ANOVA, followed by Tukey’s multiple comparisons test. Data presented as mean ± SEM. J The bar diagram quantifies the number of disintegrated organoids in each batch. At least three hundred (n = 300) organoids were randomly sampled across four independent batches (N = 4).
We noticed that hiPSC readily settled within a day of plating in our spherical plate, even without a centrifugation step. This suggests that our spherical plate may provide a more suitable environment for sphere formation (Fig. 1B). Typically, using our spherical plates, we could differentiate 10,000 hiPSC into uniform-sized 3D neurospheres within each microwell. While using a Rho-kinase (ROCK) inhibitor at this stage will alleviate cell death, prolonged exposure could change the cell’s metabolism and induce the meso-endodermal differentiation pathway28,29. Indeed, prolonged use of ROCK inhibitors is associated with generating organoids with ectopically active cellular stress pathways21. Therefore, after 24 h of initial culturing in a neural induction medium, we omitted the ROCK inhibitor.
On day 5, we noticed uniform-sized neurospheres. Imaging them revealed that they are highly similar from well to well, exhibiting characteristic neural rosette organization with primary cilia emanating apically into the lumen. Furthermore, neurosphere size remained consistent across several independent batches (Fig. 1C, E). We then transferred these uniform-sized Matrigel-free neurospheres to spinner bioreactors containing 75 ml neurosphere medium (Fig. 1D, E, F, Supplementary Table 1). After culturing for four days, we switched to a brain organoid differentiation medium containing 5 µM SB431542 and 0.5 μM Dorsomorphin, inhibitors of TGF-β and BMP pathways to initiate an undirected neural differentiation. Twenty-one days later, we switched to a brain organoid maturation medium and cultured organoids until day 150 with a constant spinning rate of 25 RPM without noticing disintegrated spheroids (Supplementary Movie 1).
To assess the overall versatility of the Hi-Q approach, we generated organoids from six independent hiPSC lines (Four healthy and two derived from microcephaly patients). Notably, in this approach, the organoids grew in size progressively over time (Fig. 1G) (except organoids derived from microcephaly patients, which are described later). In this Hi-Q platform, we generated ~15,373 organoids across 39 batches (Supplementary Table 2). Measuring 300 randomly selected Hi-Q brain organoids across four hiPSC lines revealed that organoid size was highly consistent within a batch and across hiPSC lines (Fig. 1H). Furthermore, the organoids showed a consistent and proportional size increase from day 20 to 60 across all hiPSC lines. This indicates that organoids do not aberrantly vary in growth with our Hi-Q approach (Fig. 1I). In all cases, the organoids displayed high integrity as we detected only one or two disintegrated organoids in a batch of 300 (Fig. 1J). These results suggest that the Hi-Q approach is robust, versatile, and easy to handle.
Time-resolved single-cell RNA-sequencing of Hi-Q brain organoids reveals similar cell diversities and is free from ectopic stress-inducing pathways
To dissect the cell diversity of Hi-Q brain organoids and correlate it to the human brain, we performed single-cell RNA-sequencing (scRNA-seq). First, to test similarities across independent Hi-Q brain organoids, we sequenced and compared Day 25 Hi-Q brain organoids across three independent batches (Supplementary Fig. 1). To assess the similarities between the batches, we standardized the comparison using the 2000 most highly variable genes across the batches. We then applied the k-nearest neighbor network (knn) approach to analyze distances and progression of transcriptional changes among cells in the 2D representation30,31. The knn approach used a PCA embedding (Supplementary Fig. 1A, B). In this analysis, the cells did not cluster by batches, suggesting the degree of similarity is high, or the presence of low covariance across the batches, and hence no correction was required for batch-to-batch variation. To ease the analysis of the similarities between batches, we chose three major cell types: progenitors (based on SOX2, GLI3, and PAX6), cycling progenitors (based on MKI67, CENPF, and NUSAP1), and early neurons (based on DCX, NCAM, and GAP43). We then analyzed the differences between the proportions of cells in each cell type across the batches (Supplementary Fig. 1C–E). This analysis did not yield significant differences, indicating a low batch-to-batch variation in cell types and proportions in our Hi-Q brain organoids.
To dissect the cell diversity changes across various age groups, we analyzed 16,228 cells isolated from three organoids at each time of day: 60, 90, and 150. The sequenced cells belonged to cell types such as proliferating radial glia (Pro-RG) cells expressing TTYH1, intermediate precursor cells (IPC) expressing MKI67 and NUSAP1, inhibitory neurons (IN) expressing GAD2, and excitatory neurons (EN) expressing NEUROD2 and NEUROD6 (Fig. 2A, Supplementary Fig. 2A–C). We then applied the knn approach to analyze distances and progression of transcriptional changes. All three stages of organoids comprise structural, immature, proliferating, and neuronal populations (Fig. 2A–C). Notably, cells annotated as proliferating radial glia cells (RG) and IPCs correspond to the cells in the S and G2/M phases (Supplementary Fig. 2D, E).
A Force Altas (FA) 2D representation of the neighbor graph of Hi-Q brain organoids at different time points of development (Day 60, 90, and 150). Cells are colored according to the label with the highest score given by the Lasso logistic regression model trained on primary brain data31. B Histogram plot reporting the proportion of different cell types at different time points of development. C, D FA representation of the neighbor graph of the integrated datasets from all stages. In panel (C), clusters are annotated using the expressed gene markers: Pro-RG, proliferating radial glia; AP, apical progenitors; RG, radial glia; A/O, astrocytes, and oligodendrocytes; IPC, intermediate precursor cells; Dev-N, developing neurons; Dev-HB, developing hindbrain; EaN, early neurons; EN, excitatory neurons; IN, inhibitory neurons. In panel (D), cells are colored according to the time they were sampled. E The subset of the whole integrated dataset, except the pro-RG cluster, colored by pseudotime, showing the two trajectories of developing IN (green arrow) and EN (blue arrow). The scatter plots show the expression range of characteristic IN and EN genes for each cell in function of the pseudotime. F Violin plots compare the level of expression of PGK1, ARCN1, and GORASP2, as well as the cumulative score between Hi-Q brain organoids (nine organoids from three different age groups used in Fig. 2B), other brain organoids21,30, and primary data from the literature. The overlaid box indicates median, quartiles, and 1.5× IQR whiskers; outliers are individual points.
We then used the annotated cell types to evaluate the degree of similarities and maturation at each stage of Hi-Q brain organoids. First, we noticed that individual organoids showed similar cell proportions at the same age. Next, as the organoids progressively matured, we observed an accumulation of mature neuronal types, especially excitatory neurons (EN), in day 90 and 150 organoids (Fig. 2B). We then applied principal component analysis to assess the organoids’ similarities at the transcriptional level within an age group. Importantly, this analysis revealed that the cellular composition of individual organoids exhibited a high similarity with organoids from the same age groups and widely differed from other age groups, indicating that the Hi-Q approach generates highly reproducible organoids and is reliable (Supplementary Fig. 2F). Analyzing the cell types computed from the –knn analysis that integrated cell diversities of all three age groups of organoids highlighted the presence of apical neural progenitors (AP), radial glia (RG), proliferating radial glia (Pro-RG), astrocytes and oligodendrocytes (A/O), intermediate precursor cells (IPC), developing neurons (Dev-N), developing hindbrain (Dev-HB), early neurons (EaN), excitatory neurons (EN) and inhibitory neurons (IN) (Fig. 2C, D).
To further analyze the developmental trajectories of terminally developed populations within the dataset, we used a pseudotime analysis based on diffusion from the RG cluster (Fig. 2E). The gene expression patterns across the two trajectories agree with the unbiased, calculated markers from the cell types. We observed mainly two trajectories. The first trajectory (blue line) expressing markers of dorsal telencephalon development (GLI3, EOMES, and GRIA2) leads to the formation of ENs. The second trajectory (green line), expressing markers of ventral telencephalon development (CCND2, DLX5, GAD2)30, concludes with the appearance of INs (Fig. 2E and Supplementary Fig. 2G, H).
Recent work reported that activation of cellular stress pathways in organoids interferes with the developmental process required to generate distinct cell identities of the human brain21. Thus, optimizing a method that allows the generation of brain organoids free from cellular stress pathways is critical. To test if Hi-Q brain organoids are free from those ectopic stress-inducing pathways, we analyzed the expression level of previously described stress markers PGK1, ARCN1, and GORASP221. Notably, Hi-Q brain organoids showed a lower stress marker expression than published brain organoid datasets but slightly higher than adult human brain datasets21,30 (Fig. 2F). This analysis indicates that our in vitro culture does not yet meet the natural conditions mimicking brain development in vivo. Yet, it is relatively free from ectopically activated cellular stress pathways, which impairs cell-type specification. In summary, our temporally resolved sc-RNA-sequencing data reveal that the Hi-Q approach can generate brain organoids with reduced levels of culture-induced stress and reproducible levels of cell diversity closer to an in vivo situation.
We then analyzed whether Hi-Q brain organoids exhibit cell types comparable to those generated through EB formation. To this end, we computed the major cell types and their proportions of age-matched Hi-Q brain organoids and EB-based brain organoids. To compare 60-day-old organoids, we used raw sc-RNA counts and gene expression matrices from a published study32. For comparing 90- and 150-day-old organoids, we used a data set from a different study that offered processed sc-RNA data from 90- and 180-day-old organoids7. Notably, these studies emerged from donor hiPSC that differ from ours. Our integrated analysis identified six major cell types: neurons (DCX, or STMN2), radial glia (SOX2, PAX6, HES1, GLI3, or TTYH1), proliferating radial glia (MKI67, TOP2A, NUSAP1, or CENPF), astrocytes (S100B, GFAP, AQP4, ID3, IL33, or GJA1), and inhibitory (GAD2, GAD1, SIX3, DLX6-AS1, DLX1, DLX2, DLX5, SCGN, or ISL1) and excitatory neurons (SLC17A7, SATB2, NEUROD2, or EMX1), cell lineages emerge from both ventral and dorsal brain in both organoid groups (Supplementary Fig. 3A). When calculating the relative proportions of the cell types, our analysis revealed that organoids differentiated via EBs have abundant astrocytes. On the other hand, Hi-Q brain organoids contained an increased proportion of proliferating cell types (Radial glia and proliferating radial glia) (Supplementary Fig. 3B). These findings suggest that although Hi-Q brain organoids harbor similar cell types of EB-based brain organoids, they contain more proliferative cell populations and are slightly behind the maturation status of those emerging from EBs.
Hi-Q brain organoids progressively develop over time and reveal mature neuronal markers
Next, we analyzed the cytoarchitecture of the organoids using histology. We selected a panel of markers for each cell type in organoids derived from the IMR90 on day 20 and day 60 and quantified them. Our selected panel included Nestin and SOX2 (progenitors), DCX (early neurons), Acetylated α-tubulin (neurons and cilia), Arl13b (cilia), Actin (neurons), TUJ-1 (pan-neuronal), MAP2 (cortical neurons), CTIP2 (layer 4 and 5-specific), Tau (cortical neurons), PCP4 (Purkinje neurons), GAD67 (glutamatergic neurons), Synapsin-1 (presynaptic), and PSD95 (post-synaptic). As previously described, we conducted whole-mount immunostaining and confocal imaging of intact organoids after tissue clearing to preserve organoid integrity33,34.
Day 20 organoids mainly exhibited early developmental markers of progenitors and early neurons and barely showed distinct cortical plates decorated by mature neuronal markers. Neuronal markers such as MAP2 and TUJ-1 were expressed but only localized in the cell body and did not entirely segregate into axons, indicating that these organoids are at the early stage of neuronal differentiation (Fig. 3A). In contrast, day 60 organoids were more prominent in size and exhibited an enriched level of mature neuronal markers with distinguishable cortical plates of similar thickness. Likewise, the proportions of cortical and layer-specific neurons increased with time, with Tau, PCP4, PSD95, Synapsin 1, and CTIP2-positive cells increasing in day 60 organoids (Fig. 3B–E, Supplementary Fig. 4B, and Supplementary Movie 2–14). Finally, to test if Hi-Q brain organoids could show different layers of cortex organization, such as ventricular zone/subventricular zone (VZ/SVZ) and outer SVZ (oSVZ), we tested and quantified for the expression of respective identity markers in our sc-RNA seq data. These included VZ markers (such as EMX2 and PAX6), SVZ markers (TBR2), and oSVZ markers (GFAP, TNC, PTPRZ1, FAM107A, HOPX, and LIFR)35 (Supplementary Fig. 5A–C). To experimentally validate the presence of these cell types, we stained the organoid slices for SVZ (TBR2) and oSVZ (PTPRZ1 and phospho-Vimentin) markers (Supplementary Fig. 5D–F). These data indicate that whole-brain organoids cultured via the Hi-Q approach generate cell types of the early brain and differentiate into mature cell types distinct from the early brain’s germinal zones.
A, B Tissue clearing and wholemount staining of day 20 (Ai-iv) and 60-day (Bi-iv) old organoids show that Hi-Q organoids mature over time. SOX2 and Nestin label NPCs at the ventricular zone (VZ), DCX, Acetylated tubulin, MAP2, TUJ-1, PCP4, and Tau mark neurons at the cortical plate (CP). Note cell body localization of acetylated α -tubulin, MAP2, and TUJ-1 (Arrows in Aii-iii) on day 20, organoids are remodeled into defined cortical plates (CP) on day 60 organoids (Bi-iii). Likewise, the cortical neuronal markers Tau and PCP4 were remodeled into distinct cortical plates in day 60 Hi-Q brain organoids (Aiv-Biv). Therefore, CPs are primitive or thin on day 20, and thick and distinct on day 60. Representative images are shown, and panels show scale bars. Diagrams quantify size differences between time points derived from at least 300 organoids (n = 300) from three independent batches (C), VZ diameter (D), and CP thickness (E). At least 100 organoids (n = 100) across several batches have been sampled for size comparison. At least 25 independent brain organoids (n = 25) have been sampled for VZ and CP thickness. Statistical analysis was carried out by One-way ANOVA, followed by Tukey’s multiple comparisons test, ***P < 0.001. Data presented as mean ± SEM.
Spontaneous activity and neuronal networks in Hi-Q brain organoids
Next, we investigated whether Hi-Q brain organoids exhibit functional activity and form active neuronal networks. A reliable indicator for neuronal activity and network formation in the developing and mature brain is intracellular Ca2+ signaling36. To probe for functional activity, we performed imaging of intracellular Ca2+ in brain organoids at days 30, 40, 50, and 150. To this end, we loaded the organoids with the calcium indicator dye Oregon Green BAPTA1-AM (OGB-1) by bolus injection, staining essentially all cell bodies in the field of view (Fig. 4A). Live imaging of OGB-1 fluorescence revealed vivid spontaneous intracellular Ca2+ signaling in all preparations and stages analyzed (Fig. 4B), with roughly half of all cells (42–54%) being active in the investigated age groups (Fig. 4C). Ca2+ signals were variable in amplitude and duration. We detected both single transients, lasting 10–20 s, and burst-like events, lasting 1–2 min, at each stage. Moreover, ultra-slow Ca2+ fluctuations were observed, to which faster events usually added on (Fig. 4B). The activity was not generally synchronized across the cells in the field of view, although single events occasionally occurred in several cells simultaneously (see asterisks in Fig. 4B).
A Fluorescence intensity image of an organoid loaded with the calcium indicator OGB-1. B Exemplary traces of single cells revealing spontaneous calcium signaling in day 40 and day 150 old brain organoids. Asterisks highlight occasional synchronized activity. Wash-in of tetrodotoxin (TTX; 1 µM) strongly dampens spontaneous calcium signaling. C Pie charts illustrating active and inactive cells in brain organoids across all age groups (days 30, 40, 50, and 150). D Box plots showing median (line), mean (square), interquartile range (box), and standard deviation (whiskers) of the frequency of spontaneous calcium activity under control conditions and in the presence of TTX on day 40, 50, and 150 old brain organoids. Data are from three independent batches of the organoids in each age group, each containing at least four organoids (n = 4). Gray diamonds represent single data points/cells analyzed. E Intracellular calcium transients evoked by bath application of 1 mM glutamate (upper row) or 1 mM GABA (lower row) under control conditions and in the presence of ionotropic glutamate receptor inhibitors (APV for NMDARs and NBQX for AMPARs) or the presence of inhibitors of voltage- ion channels (TTX for Nav and NiCl2 for Cav) in day 50 brain organoids. Gray traces show individual cellular responses in one particular experiment; black traces are averages of the individual traces. F Box plots showing median (line), mean (square), interquartile range (box), and standard deviation (whiskers) glutamate- or GABA-induced calcium responses of day 50 brain organoids in control conditions and in the presence of indicated receptor/channel blockers. Data are from three independent batches of the organoids, each containing at least five organoids (n = 5). Gray diamonds represent single data points/cells analyzed. Gray diamonds are single data points/cells analyzed. For (D, E), data are presented in Tukey box-and-whisker plots indicating median (line), mean (square), interquartile range (IQR; box), and standard deviation (whiskers). In addition, all individual data points are shown in gray underneath the Tukey plots. Data were statistically analyzed using one-way ANOVA followed by a post hoc Bonferroni test. The following symbols are used to illustrate the results of statistical tests in the figures: *: 0.01 ≤p < 0.05; **: 0.001 ≤p < 0.01; ***: p < 0.001. “n” represents the number of cells analyzed; “N” means the number of individual experiments/brain organoids. Each series of experiments was performed on at least three different organoids.
In organoids on days 40, 50, and 150, spontaneous activity was strongly dampened (p = 1.39E–14; p = 7.96E–34; p = 3.88E–48) in the presence of tetrodotoxin (TTX; 1 µM) that blocks voltage-gated Na+ channels, suggesting that Ca2+ signals were mostly secondary to action potential generation and activation of voltage-dependent Ca2+ channels (Fig. 4D). Next, we applied the neurotransmitters glutamate and GABA by bath perfusion for 10 s to further characterize functional activity in brain organoids. Notably, in day 40, day 50, and 150-day-old organoids, all cells tested responded to the application of 1 mM glutamate (day 40: N = 3, n = 200; day 50: N = 3, n = 142; day 150: N = 3, n = 230) or 1 mM GABA (day 40: N = 3, n = 173; day 50: N = 3, n = 211; day 150: N = 3, n = 218) with large and long-lasting Ca2+ transients (Fig. 4E, F). Glutamate-induced Ca2+ signals at day 50 were significantly reduced by the application of blockers of the NMDA-receptor blocker APV (100 µM) (N = 3, n = 133; p = 2.84E-12), and further dampened by combined application of APV with the AMPA-receptor blocker NBQX (50 µM) (N = 3, n = 108; p = 3.50E–29) (Fig. 4E, F). Ca2+ transients induced by GABA application were significantly reduced upon inhibition of action potential generation by TTX (N = 3, n = 204; p = 3.85E–14), and nearly completely suppressed by additional perfusion with NiCl2. Taken together, these results indicate that Hi-Q brain organoids develop functionally active neural networks with cells expressing voltage-gated, TTX-sensitive Na+ channels and voltage-gated Ca2+ channels, major hallmarks of differentiated neurons. Moreover, cells respond to glutamate and GABA, the brain’s primary neurotransmitters. Using pharmacological tools, we also obtained evidence for the functional expression of ionotropic glutamate receptors, namely AMPA- and NMDA receptors. Finally, the sensitivity of GABA-induced Ca2+ signals to TTX, and NiCl2 indicates that Ca2+ transients evoked by bath application GABA were secondary to cellular depolarization upon activation of ionotropic GABAA receptors37,38.
Hi-Q brain organoids can be cryopreserved, thawed, and re-cultured
Unlike patient-derived liver and intestine organoids, brain organoids have not been cryopreserved, thawed, and re-cultured, an aspect that limits the flexible and economical use of brain organoids39,40. We could successfully freeze 18-day-old Hi-Q brain organoids and cryopreserve them in liquid nitrogen. After three months of cryopreservation, we re-cultured them after thawing and analyzed them for recovery (Fig. 5A, see “Method” section). Notably, 18-day-old organoids predominantly contain undifferentiated proliferating SOX2-positive progenitors exhibiting TUJ-1-positive primitive cortical plate. To re-culture the organoids, we first thawed them into the organoid culturing medium for 48 h in a stationary petri dish and then cultured them in spinner flasks for several days (Fig. 5B). Although 48 h post-thawing, organoids did appear slightly deformed, twelve days after re-culturing (30-day-old organoids), the organoids were morphologically similar to control organoids that had never been frozen. Notably, thawing and re-culturing did not cause a significant disassociation or change in size (Fig. 5C, D). Importantly, we could also thaw and culture organoids in a petri dish without involving a spinner flask. Although the initial growth rate of thawed organoids was slower than that of the controls, they followed a growth profile similar to that of the control organoids (Supplementary Fig. 6A, B). Calculating the percentage recovery, we could obtain at least 75% of the recovery after thawing. In most cases, we could recover at least 90% of the organoids (Supplementary Fig. 6C). The differences in the frequencies of dead cells and cytoarchitecture between 48 hrs and 10 days after the thawing of organoids indicated the successful recovery of surviving cells after cryopreservation (Supplementary Fig. 6D, E).
A A schematic summarizes the cryopreservation and freeze-thawing of Hi-Q brain organoids. B Eighteen-day-old organoids before cryopreservation. TUJ-1 marks early neurons (green), TUNEL (red) shows the dead cells at the periphery, and SOX2 labels NPCs (magenta)—representative images from at least six experiments from three independent batches of neurospheres. Panels show the scale bar. C Hi-Q organoids 24 h after thawing (i) are still intact. After 48 h of thawing (ii), organoids show a slightly deformed edge. The panel shows the scale bar. D Day 30 Hi-Q organoids that have never been cryopreserved (i). The right panel (ii) shows a group of organoids after thawing. The color differences are due to different microscopes with filter settings. The panel shows the scale bar. (iii) At least eighty (n = 80) organoids from three independent batches (N = 3) were thawed and analyzed. One-way ANOVA carried out statistical analysis. There are no significant differences in the size of Hi-Q brain organoids between controls (never frozen) and freeze-thawed. Student’s t test carried out statistical analysis. Data presented as mean ± SEM. E, F Comparison of the cytoarchitecture of day-30 (E) Hi-Q brain organoid (control, never frozen) (i) and frozen and thawed organoid (ii). Magnified panels at the bottom show a ventricular zone (VZ) with its typical cytoarchitecture of early neurons (primitive cortical plate, green marked by TUJ-1) and proliferating NPCs (magenta marked by SOX2). TUNEL (red) labels dead cells; there is no difference between control and freeze-thawed organoids (n = 12) across two independent batches (N = 2) (iii). Panel (F) shows the cytoarchitecture of 60-day-old organoids stained with SOX2 (green) and Synapsin1 (red). Panels show scale bars. At least two randomly chosen organoids across two independent batches (N = 2) were compared to Day 20 controls.
We then analyzed the integrity and composition of cytoarchitectures after thawing and re-culturing. We immunostained them for SOX2, TUJ-1, and TUNEL, which labels NPCs, primitive cortical plates, and dead cells, respectively. Our analysis revealed that the re-cultured organoids exhibit strikingly similar cytoarchitectures to age-matched control groups, which were not cryopreserved and re-cultured. Notably, there was no difference in the frequencies of TUNEL-positive cells (Fig. 5E, Supplementary Fig. 6, and Supplementary Movie 15–17). By day 60, thawed and re-cultured organoids displayed synapsin-1-positive mature neuronal types and architectures indistinguishable from control organoids, which were never cryopreserved (Fig. 5F).
In contrast to 18-day-old organoids, we could not successfully re-culture day 35 or 40-old brain organoids frozen similarly. Notably, these organoids displayed a damaged cytoarchitectural organization containing massively elevated TUNEL-positive cells, indicating that they did not recover after thawing (Supplementary Fig. 6F). These data suggest that organoids generated with the Hi-Q platform are amenable to cryopreservation at an early stage of differentiation and are viable and healthy after thawing and re-culturing.
Patient-derived Hi-Q brain organoids can recapitulate distinct forms of genetic brain disorders
There are more than 10,000 rare genetic diseases, and their cumulative incidence is higher than diabetes, ranging from 3.5 to 8% of the population. Notably, many of them affect brain development with poor prognoses and no cure due to the lack of mechanistic insights into disease-relevant tissue systems exhibiting various cell types and cytoarchitectures similar to the developing brain41,42,43. Since Hi-Q brain organoids possess these characteristics, we tested their versatility in modeling distinct forms of neurogenetic diseases. Firstly, we analyzed a primary microcephaly condition due to a loss-of-function homozygous mutation in a centrosome protein CDK5RAP2. To generate primary microcephaly hiPSC, we reprogrammed patient skin fibroblasts carrying a homozygous mutation in CDK5RAP244 (Supplementary Fig. 7A–C). Second, we modeled progeria-associated Cockayne syndrome using hiPSC derived from a patient exhibiting Cockayne syndrome (also known as Cockayne syndrome B, CSB). CSB exhibits severe neurological defects caused by a mutation in ERCC6 (also known as Cockayne syndrome B, CSB). CSB is a protein implicated in the transcription-coupled nucleotide excision repair pathway in DNA damage45,46,47. CSB-related microcephaly is a secondary microcephaly. In contrast to primary microcephaly, where the brain size is small by birth, in secondary microcephaly, the cessation of the brain growth occurs postnatally.
Although we used the same number of hiPSC (Healthy control, CDK5RAP2-mutated, and Cockayne syndrome) to generate Hi-Q brain organoids, age-matched (30-day old organoids) CDK5RAP2 patient-derived organoids (Hereafter CDK5RAP2 organoids) were smaller in size. On the other hand, organoids generated from CSB patient-derived hiPSC (hereafter CSB-Organoids) were more prominent in size which dramatically collapsed at later time points, indicating that cellular functions leading to neural epithelia formation are abnormal in both models (Fig. 6A). In addition, immunostaining for SOX2-positive progenitors and TUJ1-positive early neurons on 30-day-old Hi-Q organoids revealed that control organoids displayed structurally organized ventricular zones (VZ) abundant with progenitors in a compact organization and a layer of neurons forming a primitive cortical plate (Fig. 6Bi). In contrast, CDK5RAP2 organoids revealed structurally compromised VZs with reduced diameter, less compact progenitors’ organization, and a dispersed cortical plate with TUJ1-positive neurons spreading through organoids (Fig. 6Bii).
A Comparison of healthy control (IMR90) and Hi-Q brain organoids derived from mutant patients harboring mutations in CDK5RAP2 and Cockayne syndrome B gene (CSB 739) (i-iii). CDK5RAP2 brain organoids (ii) are microcephalic as they are significantly smaller than healthy organoids. On the other hand, CSB organoids are significantly larger than healthy controls. The panel shows the scale bar. At least twenty (n = 20) randomly chosen day 30 organoids were analyzed across three independent batches (N = 3). Statistical analysis was carried out by One-way ANOVA, followed by Tukey’s multiple comparisons test, ***P < 0.001. Data presented as mean ± SEM. B Tissue sections of healthy control (IMR90), CDK5RAP2, and CSB 739 brain organoids (i-iii). The magnified panel under each variety shows VZ. SOX2 labels NPCs, and TUJ-1 marks primitive cortical plate (CP). Compared to healthy organoids (IMR90), CDK5RAP2 organoids have slightly disorganized and smaller VZ. Bar graphs at the bottom quantify the average number of VZs and their diameter in each kind. Panels show the scale bar. At least twenty sections (n = 20) from three different organoids of each group were analyzed. Statistical analysis was carried out by One-way ANOVA, followed by Tukey’s multiple comparisons test, ***P < 0.001. Data presented as mean ± SEM. C CSB 739 (iii) but not healthy (i) or CDK5RAP2 (ii) organoids display a significantly increased level of pH2AX-positive nuclei (magenta) indicative of DNA double-stranded breaks. The bar graph at the right quantifies the relative proportions of pH2AX-positive nuclei. Panels show the scale bar. An average of at least twenty sections (n = 20) from three different organoids of each group was considered. Statistical analysis was carried out by One-way ANOVA, followed by Tukey’s multiple comparisons test, ***P < 0.001. Data presented as mean ± SEM. D CSB 739 (iii) but not healthy (i) or CDK5RAP2 (ii) organoids display a significantly increased level of TUNNEL-positive cells (magenta) indicative of dead cells. The bar graph quantifies the relative proportions of TUNNEL-positive nuclei. An average of at least twenty sections (n = 20) from three different organoids of each group was considered. Statistical analysis was carried out by One-way ANOVA, followed by Tukey’s multiple comparisons test, ***P < 0.001. Data presented as mean ± SEM. Panels show the scale bar. E Hi-Q brain organoids reveal the kinetics of the apical progenitor division plane. P-Vimentin selectively labels the dividing apical progenitors at the VZ’s apical side. Healthy brain organoids (IMR90) predominantly display dividing progenitors whose division plane is horizontal to the VZ lumen (i). In contrast, CDK5RAP2 brain organoids (ii) harbor apical progenitors whose division plane is mainly vertical to the VZ lumen. The bar diagram quantifies the distribution of the division plane. H, horizontal. V, vertical. A schematic at the right shows horizontal and vertical division planes. An average of at least fifteen sections (n = 15) from three different organoids of each group was considered. Statistical analysis was carried out by One-way ANOVA, followed by Tukey’s multiple comparisons test, *P < 0.1. Data presented as mean ± SEM. Panels show the scale bar.
CSB organoids (CSB 739), on the other hand, did not exhibit recognizable VZs, and the progenitors were less densely packed and randomly distributed with weakly positive SOX2 cells. Moreover, TUJ-1 positive neurons did not form a distinct cortical plate; instead, they were broadly diffused in the organoid tissue, suggesting that brain organization is perturbed in CSB organoids (Fig. 6Biii and Supplementary Fig. 7D–F). Finally, turning our analysis for spontaneous DNA damage and apoptotic cell deaths, we noticed that CSB-organoids harbored many pH2AX-positive and TUNEL-positive cells (Fig. 6C, D). These findings revealed that without functional CSB, neural tissues undergo extensive DNA damage, thereby perturbing brain organization.
Notably, neither DNA damage nor cell death appears to cause microcephaly in CDK5RAP2 organoids, as we did not notice a significant increase in pH2AX-positive cells and TUNEL-positive cells (Fig. 6C, D). Thus, we reasoned that the microcephalic phenotype of brain organoids could be due to defective NPC maintenance, leading to premature differentiation of NPCs and NPC loss. To test this, we analyzed the kinetics of NPCs proliferation by analyzing the division plane of p-Vimentin-positive apical progenitors that form the lumen of the VZ. In contrast to controls, which harbored increased frequencies of horizontally oriented mitotic NPCs, we identified that patient-derived organoids harbored mostly vertically oriented mitotic NPCs. This indicated an unscheduled switching of the division plane, leading to premature differentiation with depletion of progenitors (Fig. 6E). This finding is similar to findings observed in EB-based organoids that have modeled microcephaly due to CDK5RAP2 mutation9, explaining that the loss of CDK5RAP2 perturbs the horizontal orientation of the spindle in the patient tissues, which is crucial for the symmetric expansion of the NPCs pool. These comparative analyses indicate that the Hi-Q brain organoids are robust in modeling distinct neurodevelopmental disorders.
Hi-Q brain organoids model glioma invasion and are amenable to medium-throughput compound screening
Glioblastoma (GBM) is an aggressive form of brain tumor with a poor prognosis. GBM harbor glioma stem cells (GSCs) that infiltrate the brain and account for the fatal nature of this disease for which there is no promising cure48,49,50. Clinically, the diffusive neuroinvasive behavior of GSCs in the human brain remains unpredictable51,52. This could be due to the lack of a physiologically relevant pre-clinical human in vitro system that can reliably recapitulate GSC invasion behaviors. Brain organoids serve as a 3D substrate for GSC and reveal the neuro-invasion behavior of GBM34,53. Conventionally, GSC cultures can be used for compound screening to kill or stop GSC proliferation in 2D. On the other hand, utilizing a brain tissue-like system is can identify the compound that can stop the neuroinvasive behavior of GSCs.
Therefore, we designed an assay to precisely measure the GSC invasion into 3D brain organoid tissues and identify compounds that can perturb the GSC invasion. Although brain organoids hold promise for 3D-organoid-based compound screening, it requires generating a high quantity of organoids with increased homogeneity to arrive at statistically significant results54. As Hi-Q brain organoids satisfy this prerequisite, we attempted to develop a proof-of-principle experiment adapting Hi-Q brain organoids for a medium-throughput drug screen.
First, we determined whether Hi-Q brain organoids can reveal the neuroinvasion behavior of patient-derived GSC. We then aimed to adapt GSC-invading organoids for a drug screening assay to identify compounds inhibiting the GSC invasion in the brain tissue. We labeled a patient-derived GSC line (#450) with mCherry and adapted our recently established brain organoid-based GBM invasion assay to Hi-Q brain organoids33,34. Importantly, Hi-Q brain organoids could faithfully recapitulate the invasive behavior of GSCs. In brief, when 5000 suspended GSCs or GSC spheroids were applied to day-50 Hi-Q brain organoids, GSCs adhered to the surrounding organoids within 24 h. Within 24–72 h, GSCs infiltrated the organoids, exhibiting typical in vivo glioma invasion characteristics, such as protrusions with extended microtubes55 (Fig. 7A, B). Using this setup, we screened compounds that could prevent the neuro-invasion property of GSCs.
A Experimental scheme for a glioma invasion assay using Hi-Q brain organoids that can be adapted for drug screening. B Hi-Q brain organoids allow GSC invasion as spheres (i) or single cells (ii). The magnified panel at the right shows invading GSCs with their typical protrusions into the organoid tissues (arrows). The bar diagram at the right quantifies the depth invaded by GSCs. Shown are representative images from at least six experiments from three independent batches of organoids. Panels show the scale bar. C, D Assay design adapted to screen the compounds preventing GSC invasion. Representative images showing invading GSC into Hi-Q brain organoids (C). At least 12 organoids (n = 12) from three independent experiments were analyzed. Statistical analysis was carried out by One-way ANOVA, followed by Tukey’s multiple comparisons test, ***P < 0.001. Data presented as mean ± SEM. Automated imaging and computer-based counting of GSC spots in each organoid. Two organoids were tested for each compound. The algorithm assigns a space when there are no invading GSCs. Dark blue denotes more GSC spots in organoids. Each box represents a well that is supplied with a compound (D). E Dot plot shows the selected compounds that prevent GSC invasion into organoids. Each dot denotes the number of GSC spots in organoids. The table at the right lists selected ten compounds that can stop the GSCs’ invasions into brain organoids. The biological functions of each compound are also listed. F Quantitative 3D imaging of GSCs invasion into brain organoids. The top panel shows the GSC invasion from spheres. The bottom panel shows GSCs invasions from GSCs suspension. Fulvestrant and Selumtinib significantly prevent GSC invasion into brain organoids as selected compounds. The invaded GSC (as spheres or single cells) were marked with red arrowheads. White arrowheads point to the spheres or cells that fail to invade the organoids in the presence of drugs. Panels show the scale bar. The bar diagram quantifies the inhibitory effects of the selected compounds on GSC invasion. Average measurements from at least ten organoids (n = 10) per drug condition were considered. Statistical analysis was carried out by One-way ANOVA, followed by Tukey’s multiple comparisons test, ***P < 0.001, **P < 0.01. Data presented as mean ± SEM.
We consolidated a library of 180 compounds with known biological targets to design a medium-throughput assay (Supplementary Table 3). We began the preliminary screening assay in 96-well format by incubating Hi-Q brain organoids and GSCs for 72 h with 5 µM of each compound. We imaged each invasion sample over three days with two image acquisition time points in an automated microscope programmed to acquire images at twenty-four and seventy-two hours. We used high-content image analysis to determine the invasion of GSCs into organoids. Here, spots were detected within the organoid region, and their numbers were quantified (see “Methods” section) (Fig. 7C). Via this assay, we identified sixteen compounds that negatively affected GSC invasion (Fig. 7D, E). As a secondary screen, we tested the ability of ten of these sixteen compounds (which exhibited the most inhibitory effect) to perturb GSC invasion at 1 µM concentration. This assay relied on uniform-sized organoids for comparison. This analysis identified Selumetinib and Fulvestrant as effective inhibitors of GSC invasion into brain organoids as judged by the differences in the number of GSC foci between twenty-four and seventy-two hours of invasion assay (Supplementary Fig. 8, parts 1 and 2, red dotted box in part 2). Selumetinib is a mitogen-activated protein kinase 1, and 2 inhibitors used to treat neurofibromatosis56. Fulvestrant is a selective estrogen receptor degrader (SERD) used to treat advanced breast cancer57.
We then tested whether Selumetinib and Fulvestrant compounds could perturb GSC invasion when supplied as single cells or spheres in Hi-Q brain organoids (Supplementary Fig. 9, 10, Low resolution). We then applied high-resolution quantitative 3D imaging and evaluated the abilities of these compounds in perturbing GSC invasion. Compared to vehicle control, these compounds significantly prevented the invading power of GSCs when supplied with either compact spheres or single cells (Fig. 7F). To corroborate our imaging-based data and to compute the fraction of the organoid volume occupied by GSCs, we applied a computational tool (Described in the method section). We calculated the fraction of the organoid volume occupied by GSCs (Supplementary Fig. 10D).
To test whether the drugs identified in our Hi-Q brain organoid had a significant impact in vivo, we grafted GFP-tagged GSC lines onto the striatum of NOD-SCID mice (line GSC#1 and GSC#472. Figs S11). After a week of grafting, we treated the animals for three weeks with saline or a combined 20 mg/Kg of Selumetinib and Fulvestrant. In untreated mice, both GSC lines invaded extensively at the injected striatum and spread to the white matter paths, like the corpus callosum, optic tract, anterior commissure, and cerebrospinal fluid (CSF) pathways. We imaged histological sections through the tumor epicenter to assess the invasion of the white matter and CSF paths. We analyzed the number of GSCs invading the corpus callosum, optic tract, and the walls of the ventricles in saline and drug-treated subjects (Supplementary Fig. 11). The drug treatment significantly reduced the tumor volumes of GSCs in the striatum (Supplementary Fig. 11A, E, F). Besides, the drug treatment also significantly reduced the spread of tumor spheres onto the ventricular walls and impaired the invasion of GSCs into the corpus callosum and optic tract (Supplementary Fig. 11D, E). In summary, the brain organoids generated via the Hi-Q approach are amenable to model glioma and can ultimately serve as a test system to screen potential therapeutic compounds to inhibit the invasive behavior of GSCs.
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- Source: https://www.nature.com/articles/s41467-024-55226-6