Main

Recent advances in hPSC differentiation enable the derivation of a myriad of specific subtypes of neurons on demand. However, the application of this technology remains hampered by the slow maturation rates of human cells, resulting in prolonged culture periods for the emergence of disease-relevant phenotypes. Indeed, most neurological and psychiatric disorders manifest as impairments in postnatal or adult neuron functions such as synaptic connectivity1, dendritic arborization2 and electrophysiological function3. Therefore, develo** strategies to accelerate the maturation of hPSC-derived neurons is critical to realize their full potential in modeling and treating neural diseases.

Multiple cell-extrinsic factors have been identified as contributors to neuron maturation, including glial cells4, network activity5 and neurotrophic factors6. However, within a given microenvironment, cell-intrinsic maturation rates appear dominant and determined by a species-specific molecular clock, which runs particularly slowly in human neurons7,8. For example, the maturation of hPSC-derived cortical neurons transplanted into the develo** mouse brain follows human-specific timing, requiring 9 months to achieve mature, adult-like morphologies and spine function9. Similarly, the transplantation of mouse versus pig versus human midbrain dopamine neurons into the brain of Parkinsonian rats results in graft-induced functional rescue after 4 weeks, 3 months or 5 months, respectively, indicating that transplanted cells retain their intrinsic, species-specific, in vivo maturation timing rather than adopting the timing of the host10.

In the present study, we established a multi-phenotypic, image-based assay to monitor maturation in nearly pure populations of hPSC-derived, deep-layer cortical neuron cultures and applied it to screen 2,688 bioactive compounds for drivers of maturation. Among the screening hits, compounds targeting chromatin remodeling and calcium-dependent transcription were combined into a maturation cocktail that was effective across a broad range of maturation phenotypes and multiple cell types.

Results

High-content assay of neuron maturity

The phenotypic complexity of neurons makes single-readout assays unsuitable to fully capture maturation stages. Therefore, we used a multi-phenotype approach (via high-content screening (HCS)) to design an assay that monitors multiple features of neuronal maturation in parallel (Fig. 1a). Dendritic outgrowth is a widely used parameter of neuron maturity11 and can be monitored through automated tracing of microtubule-associated protein 2 (MAP2) immunostaining (Fig. 1b,c). Changes in nuclear size and morphology are also characteristic of neuron development and maturation12 and can be tracked via DAPI counterstaining (Fig. 1b,c). As an indirect measurement of neuronal function and excitability, we quantified the nuclear expression of immediate early gene (IEG) products FOS and early growth response (EGR)-1 after 2 h of KCl stimulation (Fig. 1b,d). IEGs are defined by their rapid induction without requiring new protein synthesis by stimuli that include sustained membrane depolarization in neurons13. In contrast to more traditional measures of neuronal activity such as calcium imaging and electrophysiology, IEG immunoreactivity is readily scalable as a readout for thousands of treatment conditions. However, IEGs can be triggered by stimuli other than neuronal activity, including growth factor signaling14 and cellular stress responses15. Therefore, to avoid direct activation of IEGs, we used transient compound treatment (days 7–14) and performed all measurements after removal of compounds, followed by culture in compound-free medium for an additional 7 d (days 14–21) before analysis (Fig. 1a). Furthermore, we recorded IEGs under both basal and KCl-stimulated conditions to specifically determine the depolarization-induced signal by subtracting the baseline from KCl-induced responses. Measuring maturation readouts only after compound withdrawal enabled the identification of hits that trigger a long-lasting ‘memory’ of a maturation stimulus even 1 week after compound withdrawal.

Fig. 1: Chemical HCS for drivers of neuron maturation.
figure 1

a, Outline of screening protocol in hPSC-derived excitatory cortical neurons. 2SMAD-I, dual-SMAD inhibition. b, Example of input immunofluorescent images. Top, unstimulated neurons at day 21 post-plating. Bottom, neurons that received 50 mM of KCl 2 h before fixation. c, Automated analysis of neuron morphology. Left, nuclei detection mask from the DAPI channel. Right, automated neurite tracing from the MAP2 channel. d, Quantification of neuron excitability by applying an intensity threshold to FOS and EGR-1 channels within the nuclear mask. e, Left, PCA of screened compound library computed from six maturity parameters: nucleus area, nucleus roundness, total neurite length, number of neurite segments, FOS+ cell fraction and EGR-1+ cell fraction (z-scores averaged from n = 2 independent screens). Left, PCA plot of 2,343 nontoxic library compounds (out of 2,688 total compounds tested) with phenotypic clustering of maturation-enhancing (orange), maturation-inhibiting (blue) and non-neuronal proliferation-enhancing (gray) compounds. PC1 is primarily driven by the results from IEG induction and neurite growth, whereas PC2 is mainly driven by the nuclear size/roundness data. Right, representative screen images and ten representative hit compounds within each cluster. Scale bars, 50 μm.

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Although these readouts are pan-neuronal, and therefore appropriate across different neuronal lineages, we chose cortical neurons for the screen for both technical and biological reasons. Cortical neurons can be derived at high efficiency in the absence of expensive recombinant proteins and their even cell distribution in two-dimensional (2D) culture, free of clusters, makes them amenable to high-throughput imaging. They also represent a brain region that follows a particularly protracted timing of development and a region of great importance to human neurological disease. Our cortical neuron differentiation protocol yields enriched populations of post-mitotic deep-layer T-brain 1-positive (TBR1+) cells, which can be scaled, cryopreserved and directly thawed for use in large-scale assays (Supplementary Fig. 1a–e). To benchmark assay performance in mature cells, we employed primary embryonic rat cortical neurons, which quickly and reliably develop mature-like functionality in vitro16. At 14 d after plating, rat neurons displayed large and round nuclei (130 μm2, 0.93 roundness index), extensive neurite growth (>2,500 μm per neuron) and almost 100% of the neurons showed KCl-induced IEG responses (Supplementary Fig. 1f–j). In contrast, in hPSC-derived cortical neurons, these properties only very gradually emerged over a 50-d culture period and never reached the maturity of their rodent counterparts (Supplementary Fig. 1k–n). These results indicate that our multi-phenotypic assay reliably captures aspects of maturation in rat and hPSC-derived cortical neurons.

Chemical screen for maturation enhancers

We next applied our maturity assay to screen a library of 2,688 bioactive compounds in hPSC-derived cortical neurons (Supplementary Fig. 2a). The library was applied at 5 μM and standard scores (z-scores) of duplicate screen runs were averaged for analysis. Viability was determined by quantifying intact nuclei and 325 toxic compounds with a viability z-score <−2 were excluded from further analysis (Supplementary Fig. 2b). For HCS hit selection, we applied principal component analysis (PCA) to six maturity z-scores to identify hit patterns for compounds, avoiding single threshold hit discrimination (Fig. 1e, left). The six parameters were: nucleus size and roundness, total neurite length and branching (number of segments per cell), and fractions of KCl-induced FOS+ and EGR-1+ cells. We identified three phenotypic clusters of compounds by PCA: maturation enhancers (hits); maturation suppressors, consisting mostly of inhibitors of the phosphoinositide 3-kinase (PI3K)/protein kinase B (AKT)/mechanistic target of rapamycin (mTOR) axis; and inducers of proliferation of a non-neuronal contaminant population, which were highly enriched for transcription growth factor (TGF)-β signaling inhibitors as well as inhibitors of ρ-associated protein kinase (ROCK) and other signaling pathways (Fig. 1e, right). We selected 32 compounds within the mature cluster (PC1 > 4) for validation. Although PCA identifies compounds with the greatest overall maturation effect, we reasoned that compounds with strong effects on single parameters could also be of interest. We therefore added the top five highest scoring compounds for each, total neurite length and double FOS+/EGR-1+ cells, excluding compounds already selected by PCA (Supplementary Fig. 3a). As single-parameter readouts are susceptible to false positives, we excluded drugs with known maturation-independent effects, such as the microtubule stabilizers docetaxel and paclitaxel. Neurite-only hits included inhibitors of Aurora kinase, in agreement with recent phenotypic screens targeting this phenotype17,18. Using such combined criteria, we selected 42 primary hits for follow-up studies (Supplementary Table 1).

To validate primary hits, the 42 compounds were subjected to the maturity assay in triplicate at the screening concentration (5 μM) and ranked by their effect on 4 maturity parameters: nucleus size and roundness, total neurite length and double positivity for KCl-induced FOS/EGR-1 cells (Supplementary Fig. 3b). The 22 compounds with the highest mean normalized score over dimethyl sulfoxide (DMSO) across all parameters underwent additional dose–response studies (Fig. 2a), resulting in the identification of four compounds with the most pronounced, dose-dependent effects on the mean maturation score (Fig. 2b). These compounds consisted of two inhibitors of lysine-specific demethylase 1 (LSD1/KDM1A), an inhibitor of disruptor of telomerase-like 1 (DOT1L) and an L-type calcium channel (LTCC) agonist. As the screen was run at a concentration susceptible to off-target effects, we conducted dose–curve experiments including independent compounds targeting DOT1L and LTCC, observing dose-dependent improvements across all maturation parameters (Supplementary Fig. 4). The identification of two additional LSD1 inhibitors as hits in the primary screen obviated this step for this target.

Fig. 2: Validation and a combination of screen hits identify maturation-promoting cocktail GENtoniK.
figure 2

a, Ranking of primary hits by the mean of four maturity parameters (nucleus size and roundness, neurite length and KCl-induced double FOS+/EGR-1+ cells) normalized to DMSO (n = 3 microplate wells). The 22 top-ranked compounds were selected for validation. b, Dose–response validation of 22 screen hits comparing the mean of 4 maturity parameters normalized to DMSO (n = 15 microplate wells from 3 independent differentiations). cf, Comparison of confirmed hits GSK2879552 (G), EPZ-5676 (E), Bay K 8644 (K) and a combination of the three (G + E + K) across maturity parameter IEG induction (c), neurite growth (d), nucleus size (e) and nucleus area (f) (n = 8 microplate wells from 2 independent experiments). gj, Comparison of three-hit drug combination (G + E + K) to the same with the addition of NMDA across maturity parameter IEG induction (g), neurite growth (h), nucleus size (i) and nucleus roundness (j) (n = 8 microplate wells from 2 independent differentiations). k, Top, representative images of cortical neurons treated with DMSO or maturation-promoting cocktail GENtoniK. Bottom, formulation of GENtoniK. In a and b, Brown–Forsythe and Welch’s ANOVA with Dunnett’s T3 multiple-comparison test were used. In cj, two-tailed Welch’s t-test was used; asterisks indicate statistical significance. Mean values are represented by a bar graph (a) or a line (cj). Error bars represent s.e.m. Scale bars, 50 μm.

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Small-molecule cocktail promotes neuron maturity

LSD1 is a histone 3 demethylase at lysines 4 and 9, and a switch of specificity between these two substrates has been previously linked to neuron differentiation19,20. DOT1L is the sole methyltransferase targeting lysine 79 within the globular domain of histone 3 (ref. 21). LTCCs are involved in calcium-dependent transcription and play important roles in neuron development22. We reasoned that transcriptional induction by the LTCC agonist might act independently and further potentiate the effect of chromatin remodeling by epigenetic regulators such as LSD1 and DOT1L. Accordingly, we next sought to determine whether a combination of hits can further enhance neuron maturation. As two of the confirmed hits target LSD1, we decided to pursue only one of them, GSK2879552, for combinatorial experiments, because it displayed a stronger combined effect than OG-L002 (Fig. 2b). A combination of the three-hit compounds significantly increased IEG induction, neurite growth and nucleus size, but not nucleus roundness, compared with single-compound treatments (Fig. 2c–f).

In addition to LTCCs, calcium-dependent transcription is initiated through activation of N-methyl-d-aspartate (NMDA)-type glutamate receptors23, which have also been shown to participate in neuron maturation24. The compound NMDA itself was among the primary hits but, although significant, it was not among the 22 top hits in the single-agent validation study (Fig. 2a). Given its known role in activity-dependent transcription, we next tested whether the addition of NMDA could further enhance maturation in the presence of the above three-hit combination. We observed significant improvements across all maturity parameters (Fig. 2g–j) and nominated the resulting four drugs (GSK2879552, EPZ-5676, NMDA and Bay K 8644) as a maturation-promoting cocktail, naming it GENtoniK (Fig. 2k).

Dysregulation of both histone methylation and calcium signaling can be associated with toxicity in neurons. To determine potentially harmful effects of GENtoniK on neuronal cultures, we conducted viability and cellular stress assays in cortical neurons from WA09 human embryonic stem cell (hESC) and GM03348-induced hPSC (hiPSC) lines. Neither individual compounds nor the complete GENtoniK cocktail increased cell death compared with DMSO in a 21-d time-course analysis measuring plasma membrane integrity at the end-point (Supplementary Fig. 5a,b). In fact, a resazurin-based assay resulted in a slightly improved viability (Supplementary Fig. 5c), possibly owing to higher respiratory rates of treated neurons caused by increased surface area and metabolism. As a readout of double-strand DNA breaks, we quantified nuclear foci containing phosphorylated ATM (serine/threonine kinase), observing no difference between DMSO and GENtoniK neurons (Supplementary Fig. 6a, at 24 h post-treatment, and Supplementary Fig. 6c, at 24 h and 7 d post-treatment), but a dramatic increase in those treated with the radiomimetic drug bleomycin as a positive control. To assess potential copy number aberrations (CNAs) induced by GENtoniK treatment, we conducted shallow whole-genome sequencing (WGS), observing no difference in copy number profiles of GENtoniK- and DMSO-treated neurons (Supplementary Fig. 6c). GENtoniK also did not cause obvious aberrations in chromatin nuclear localization, as revealed by staining for markers of heterochromatin and active chromatin H3K9me3 and H3K9ac (Supplementary Fig. 6d). Similarly, there was no loss of H3K9me3 intensity or percentage positive cells by flow cytometry upon GENtoniK treatment (Supplementary Fig. 6e–h).

GENtoniK promotes functional neuron maturation

We next validated GENtoniK on additional maturation phenotypes, independent of those assayed during primary screening. Establishing independent functional readouts was particularly important, because three of the proteins targeted by the cocktail have been reported to directly participate in IEG induction in neurons25,26,https://www.brainspan.org), genes upregulated by GENtoniK displaying an average expression that increased from early development to gestation and after birth (top). trim., trimester. Genes downregulated display higher average expression during early development and decrease over time (bottom). The black line represents smoothed mean curves with bands representing confidence intervals. In c, eg and ik, two-tailed Welch’s t-test was used; asterisks indicate statistical significance. Mean values are represented by a black line (c) or a bar graph (eg and ik). Error bars represent s.e.m.

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