Ábel Vértesy

Functional neural networks emerge as developing neurons form synaptic connections. Revealing how these connections are organized and perturbed in disease requires linking single-neuron connectivity to molecular state across thousands of networks, which is challenging with current methods. We developed COSCO (Connectomics by Sequencing in Cerebral Organoids), combining barcoded monosynaptic rabies tracing with single-cell RNA sequencing to reconstruct over 10,000 networks across organoids. We demonstrate that organoid circuitry self-organizes into stereotyped network motifs governed by cell-intrinsic wiring rules aligning with features of mouse cortical connectivity. Projecting network topology onto transcriptomic space reveals that wiring correlates with cell-adhesion and synaptic gene expression programs. In a Tuberous Sclerosis Complex model, pathological hyperexcitability coincides with topological rewiring: mutant networks become more heterogeneous, driven by the transcriptional distribution of upper layer excitatory cell states. This work establishes cerebral organoids as a model to study self-organization of human connectivity, and its disruption in neurodevelopmental disease. Abstract Figure:

The small GTPase RAS is a signalling hub activating multiple pathways, which may respond differently to a constitutively active RAS mutation. We explored this issue using fission yeast, where RAS-mediated pheromone signalling (PS) activates the MAPK ^Spk1 and Cdc42 pathways. We observed that in cells with the yeast RAS mutant, ras1.G17V , the MAPK ^Spk1 activation was attenuated similarly to that in wildtype cells, whereas Cdc42 activation was prolonged. We built a mathematical model implementing PS negative-feedback circuits and competition between the two Ras1 effectors, MAPKKK ^Byr2 and Cdc42-GEF ^Scd1 . The model robustly predicted the MAPK ^Spk1 activation dynamics of an additional 20 PS mutants. In support of the model, a recombinant Cdc42-GEF ^Scd1 competed with MAPKKK ^Byr2 for Ras1 binding and overexpression of the Ras binding domain of either Cdc42-GEF ^Scd1 or MAPKKK ^Byr2 inhibited both downstream pathways. Our study has established that the constitutively active RAS signalling propagates differently to downstream pathways where the system prevents MAPK overactivation.

The development of the human brain involves unique processes (not observed in many other species) that can contribute to neurodevelopmental disorders ^1–4 . Cerebral organoids enable the study of neurodevelopmental disorders in a human context. We have developed the CRISPR–human organoids–single-cell RNA sequencing (CHOOSE) system, which uses verified pairs of guide RNAs, inducible CRISPR–Cas9-based genetic disruption and single-cell transcriptomics for pooled loss-of-function screening in mosaic organoids. Here we show that perturbation of 36 high-risk autism spectrum disorder genes related to transcriptional regulation uncovers their effects on cell fate determination. We find that dorsal intermediate progenitors, ventral progenitors and upper-layer excitatory neurons are among the most vulnerable cell types. We construct a developmental gene regulatory network of cerebral organoids from single-cell transcriptomes and chromatin modalities and identify autism spectrum disorder-associated and perturbation-enriched regulatory modules. Perturbing members of the BRG1/BRM-associated factor (BAF) chromatin remodelling complex leads to enrichment of ventral telencephalon progenitors. Specifically, mutating the BAF subunit ARID1B affects the fate transition of progenitors to oligodendrocyte and interneuron precursor cells, a phenotype that we confirmed in patient-specific induced pluripotent stem cell-derived organoids. Our study paves the way for high-throughput phenotypic characterization of disease susceptibility genes in organoid models with cell state, molecular pathway and gene regulatory network readouts.

Organoids enable in vitro modeling of complex developmental processes and disease pathologies. Like most 3D cultures, organoids lack sufficient oxygen supply and therefore experience cellular stress. These negative effects are particularly prominent in complex models, such as brain organoids, and can affect lineage commitment. Here, we analyze brain organoid and fetal single‐cell RNA sequencing (scRNAseq) data from published and new datasets, totaling about 190,000 cells. We identify a unique stress signature in the data from all organoid samples, but not in fetal samples. We demonstrate that cell stress is limited to a defined subpopulation of cells that is unique to organoids and does not affect neuronal specification or maturation. We have developed a computational algorithm, Gruffi, which uses granular functional filtering to identify and remove stressed cells from any organoid scRNAseq dataset in an unbiased manner. We validated our method using six additional datasets from different organoid protocols and early brains, and show its usefulness to other organoid systems including retinal organoids. Our data show that the adverse effects of cell stress can be corrected by bioinformatic analysis for improved delineation of developmental trajectories and resemblance to in vivo data.

Arrhythmogenic cardiomyopathy (ACM) is an inherited cardiac disorder that is characterized by progressive loss of myocardium that is replaced by fibro-fatty cells, arrhythmias, and sudden cardiac death. While myocardial degeneration and fibro-fatty replacement occur in specific locations, the underlying molecular changes remain poorly characterized. Here, we aim to delineate local changes in gene expression to identify new genes and pathways that are relevant for specific remodelling processes occurring during ACM. Using Tomo-Seq, genome-wide transcriptional profiling with high spatial resolution, we created transmural epicardial-to-endocardial gene expression atlases of explanted ACM hearts to gain molecular insights into disease-driving processes. This enabled us to link gene expression profiles to the different regional remodelling responses and allowed us to identify genes that are potentially relevant for disease progression. In doing so, we identified distinct gene expression profiles marking regions of cardiomyocyte degeneration and fibro-fatty remodelling and revealed Zinc finger and BTB domain-containing protein 11 (ZBTB11) to be specifically enriched at sites of active fibro-fatty replacement of myocardium. Immunohistochemistry indicated ZBTB11 to be induced in cardiomyocytes flanking fibro-fatty areas, which could be confirmed in multiple cardiomyopathy patients. Forced overexpression of ZBTB11 induced autophagy and cell death-related gene programmes in human cardiomyocytes, leading to increased apoptosis. Our study shows the power of Tomo-Seq to unveil new molecular mechanisms in human cardiomyopathy and uncovers ZBTB11 as a novel driver of cardiomyocyte loss. Using spatial transcriptomics, transmural epicardial-to-endocardial gene expression atlases of human ACM hearts were generated. Linking gene expression profiles to regional remodelling responses revealed Zinc finger and BTB domain-containing protein 11 (ZBTB11) to be specifically enriched at sites of active fibro-fatty replacement of myocardium. Immunohistochemistry indicated ZBTB11 to be induced in cardiomyocytes flanking fibro-fatty areas, which could be confirmed in multiple cardiomyopathy patients. This study shows the power of Tomo-Seq to unveil new molecular mechanisms in human cardiomyopathy and uncovers ZBTB11 as a novel driver of cardiomyocyte loss.

Organoids enable disease modeling in complex and structured human tissue, in vitro . Like most 3D models, they lack sufficient oxygen supply, leading to cellular stress. These negative effects are particularly prominent in complex models, like brain organoids, where they can prevent proper lineage commitment. Here, we analyze brain organoid and fetal single cell RNA sequencing (scRNAseq) data from published and new datasets totaling over 190,000 cells. We describe a unique stress signature found in all organoid samples, but not in fetal samples. We demonstrate that cell stress is limited to a defined organoid cell population, and present Gruffi, an algorithm that uses granular functional filtering to identify and remove stressed cells from any organoid scRNAseq dataset in an unbiased manner. Our data show that adverse effects of cell stress can be corrected by bioinformatic analysis, improving developmental trajectories and resemblance to fetal data.

Evolutionary development of the human brain is characterized by the expansion of various brain regions. Here, we show that developmental processes specific to humans are responsible for malformations of cortical development (MCDs), which result in developmental delay and epilepsy in children. We generated a human cerebral organoid model for tuberous sclerosis complex (TSC) and identified a specific neural stem cell type, caudal late interneuron progenitor (CLIP) cells. In TSC, CLIP cells over-proliferate, generating excessive interneurons, brain tumors, and cortical malformations. Epidermal growth factor receptor inhibition reduces tumor burden, identifying potential treatment options for TSC and related disorders. The identification of CLIP cells reveals the extended interneuron generation in the human brain as a vulnerability for disease. In addition, this work demonstrates that analyzing MCDs can reveal fundamental insights into human-specific aspects of brain development.

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The spindle assembly checkpoint (SAC) ensures proper chromosome segregation by monitoring kinetochore–microtubule interactions. SAC proteins are shed from kinetochores once stable attachments are achieved. Human kinetochores consist of hundreds of SAC protein recruitment modules and bind up to 20 microtubules, raising the question of how the SAC responds to intermediate attachment states. We show that one protein module (‘RZZS-MAD1-MAD2’) of the SAC is removed from kinetochores at low microtubule occupancy and remains absent at higher occupancies, while another module (‘BUB1-BUBR1’) is retained at substantial levels irrespective of attachment states. These behaviours reflect different silencing mechanisms: while BUB1 displacement is almost fully dependent on MPS1 inactivation, MAD1 (also known as MAD1L1) displacement is not. Artificially tuning the affinity of kinetochores for microtubules further shows that ∼50% occupancy is sufficient to shed MAD2 and silence the SAC. Kinetochores thus respond as a single unit to shut down SAC signalling at submaximal occupancy states, but retain one SAC module. This may ensure continued SAC silencing on kinetochores with fluctuating occupancy states while maintaining the ability for fast SAC re-activation.