Cell-type specific defects in PTEN-mutant cortical organoids converge on abnormal circuit activity.

De novo heterozygous loss-of-function mutations in phosphatase and tensin homolog (PTEN) are strongly associated with autism spectrum disorders; however, it is unclear how heterozygous mutations in this gene affect different cell types during human brain development and how these effects vary across individuals. Here, we used human cortical organoids from different donors to identify cell-type specific developmental events that are affected by heterozygous mutations in PTEN. We profiled individual organoids by single-cell RNA-seq, proteomics and spatial transcriptomics and revealed abnormalities in developmental timing in human outer radial glia progenitors and deep-layer cortical projection neurons, which varied with the donor genetic background. Calcium imaging in intact organoids showed that both accelerated and delayed neuronal development phenotypes resulted in similar abnormal activity of local circuits, irrespective of genetic background. The work reveals donor-dependent, cell-type specific developmental phenotypes of PTEN heterozygosity that later converge on disrupted neuronal activity.

Proper acquisition of cell class identity in organoids allows definition of fate specification programs of the human cerebral cortex.

Realizing the full utility of brain organoids to study human development requires understanding whether organoids precisely replicate endogenous cellular and molecular events, particularly since acquisition of cell identity in organoids can be impaired by abnormal metabolic states. We present a comprehensive single-cell transcriptomic, epigenetic, and spatial atlas of human cortical organoid development, comprising over 610,000 cells, from generation of neural progenitors through production of differentiated neuronal and glial subtypes. We show that processes of cellular diversification correlate closely to endogenous ones, irrespective of metabolic state, empowering the use of this atlas to study human fate specification. We define longitudinal molecular trajectories of cortical cell types during organoid development, identify genes with predicted human-specific roles in lineage establishment, and uncover early transcriptional diversity of human callosal neurons. The findings validate this comprehensive atlas of human corticogenesis in vitro as a resource to prime investigation into the mechanisms of human cortical development.

Autism genes converge on asynchronous development of shared neuron classes.

Genetic risk for autism spectrum disorder (ASD) is associated with hundreds of genes spanning a wide range of biological functions1-6. The alterations in the human brain resulting from mutations in these genes remain unclear. Furthermore, their phenotypic manifestation varies across individuals7,8. Here we used organoid models of the human cerebral cortex to identify cell-type-specific developmental abnormalities that result from haploinsufficiency in three ASD risk genes-SUV420H1 (also known as KMT5B), ARID1B and CHD8-in multiple cell lines from different donors, using single-cell RNA-sequencing (scRNA-seq) analysis of more than 745,000 cells and proteomic analysis of individual organoids, to identify phenotypic convergence. Each of the three mutations confers asynchronous development of two main cortical neuronal lineages-γ-aminobutyric-acid-releasing (GABAergic) neurons and deep-layer excitatory projection neurons-but acts through largely distinct molecular pathways. Although these phenotypes are consistent across cell lines, their expressivity is influenced by the individual genomic context, in a manner that is dependent on both the risk gene and the developmental defect. Calcium imaging in intact organoids shows that these early-stage developmental changes are followed by abnormal circuit activity. This research uncovers cell-type-specific neurodevelopmental abnormalities that are shared across ASD risk genes and are finely modulated by human genomic context, finding convergence in the neurobiological basis of how different risk genes contribute to ASD pathology.

Immortalized striatal precursor neurons from Huntington's disease patient-derived iPS cells as a platform for target identification and screening for experimental therapeutics.

We have previously established induced pluripotent stem cell (iPSC) models of Huntington's disease (HD), demonstrating CAG-repeat-expansion-dependent cell biological changes and toxicity. However, the current differentiation protocols are cumbersome and time consuming, making preparation of large quantities of cells for biochemical or screening assays difficult. Here, we report the generation of immortalized striatal precursor neurons (ISPNs) with normal (33) and expanded (180) CAG repeats from HD iPSCs, differentiated to a phenotype resembling medium spiny neurons (MSN), as a proof of principle for a more tractable patient-derived cell model. For immortalization, we used co-expression of the enzymatic component of telomerase hTERT and conditional expression of c-Myc. ISPNs can be propagated as stable adherent cell lines, and rapidly differentiated into highly homogeneous MSN-like cultures within 2 weeks, as demonstrated by immunocytochemical criteria. Differentiated ISPNs recapitulate major HD-related phenotypes of the parental iPSC model, including brain-derived neurotrophic factor (BDNF)-withdrawal-induced cell death that can be rescued by small molecules previously validated in the parental iPSC model. Proteome and RNA-seq analyses demonstrate separation of HD versus control samples by principal component analysis. We identified several networks, pathways, and upstream regulators, also found altered in HD iPSCs, other HD models, and HD patient samples. HD ISPN lines may be useful for studying HD-related cellular pathogenesis, and for use as a platform for HD target identification and screening experimental therapeutics. The described approach for generation of ISPNs from differentiated patient-derived iPSCs could be applied to a larger allelic series of HD cell lines, and to comparable modeling of other genetic disorders.

Skin-resident innate lymphoid cells converge on a pathogenic effector state.

Tissue-resident innate lymphoid cells (ILCs) help sustain barrier function and respond to local signals. ILCs are traditionally classified as ILC1, ILC2 or ILC3 on the basis of their expression of specific transcription factors and cytokines1. In the skin, disease-specific production of ILC3-associated cytokines interleukin (IL)-17 and IL-22 in response to IL-23 signalling contributes to dermal inflammation in psoriasis. However, it is not known whether this response is initiated by pre-committed ILCs or by cell-state transitions. Here we show that the induction of psoriasis in mice by IL-23 or imiquimod reconfigures a spectrum of skin ILCs, which converge on a pathogenic ILC3-like state. Tissue-resident ILCs were necessary and sufficient, in the absence of circulatory ILCs, to drive pathology. Single-cell RNA-sequencing (scRNA-seq) profiles of skin ILCs along a time course of psoriatic inflammation formed a dense transcriptional continuum-even at steady state-reflecting fluid ILC states, including a naive or quiescent-like state and an ILC2 effector state. Upon disease induction, the continuum shifted rapidly to span a mixed, ILC3-like subset also expressing cytokines characteristic of ILC2s, which we inferred as arising through multiple trajectories. We confirmed the transition potential of quiescent-like and ILC2 states using in vitro experiments, single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) and in vivo fate mapping. Our results highlight the range and flexibility of skin ILC responses, suggesting that immune activities primed in healthy tissues dynamically adapt to provocations and, left unchecked, drive pathological remodelling.

Systematic comparison of single-cell and single-nucleus RNA-sequencing methods.

The scale and capabilities of single-cell RNA-sequencing methods have expanded rapidly in recent years, enabling major discoveries and large-scale cell mapping efforts. However, these methods have not been systematically and comprehensively benchmarked. Here, we directly compare seven methods for single-cell and/or single-nucleus profiling-selecting representative methods based on their usage and our expertise and resources to prepare libraries-including two low-throughput and five high-throughput methods. We tested the methods on three types of samples: cell lines, peripheral blood mononuclear cells and brain tissue, generating 36 libraries in six separate experiments in a single center. To directly compare the methods and avoid processing differences introduced by the existing pipelines, we developed scumi, a flexible computational pipeline that can be used with any single-cell RNA-sequencing method. We evaluated the methods for both basic performance, such as the structure and alignment of reads, sensitivity and extent of multiplets, and for their ability to recover known biological information in the samples.

Author Correction: Systematic comparison of single-cell and single-nucleus RNA-sequencing methods.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

ATR is a MYB regulated gene and potential therapeutic target in adenoid cystic carcinoma.

Adenoid cystic carcinoma (ACC) is a rare cancer that preferentially occurs in the head and neck, breast, as well as in other sites. It is an aggressive cancer with high rates of recurrence and distant metastasis. Patients with advanced disease are generally incurable due to the lack of effective systemic therapies. Activation of the master transcriptional regulator MYB is the genomic hallmark of ACC. MYB activation occurs through chromosomal translocation, copy number gain or enhancer hijacking, and is the key driving event in the pathogenesis of ACC. However, the functional consequences of alternative mechanisms of MYB activation are still uncertain. Here, we show that overexpression of MYB or MYB-NFIB fusions leads to transformation of human glandular epithelial cells in vitro and results in analogous cellular and molecular consequences. MYB and MYB-NFIB expression led to increased cell proliferation and upregulation of genes involved in cell cycle control, DNA replication, and DNA repair. Notably, we identified the DNA-damage sensor kinase ATR, as a MYB downstream therapeutic target that is overexpressed in primary ACCs and ACC patient-derived xenografts (PDXs). Treatment with the clinical ATR kinase inhibitor VX-970 induced apoptosis in MYB-positive ACC cells and growth inhibition in ACC PDXs. To our knowledge, ATR is the first example of an actionable target downstream of MYB that could be further exploited for therapeutic opportunities in ACC patients. Our findings may also have implications for other types of neoplasms with activation of the MYB oncogene.

Treatment with JQ1, a BET bromodomain inhibitor, is selectively detrimental to R6/2 Huntington's disease mice.

Transcriptional and epigenetic alterations occur early in Huntington's disease (HD), and treatment with epigenetic modulators is beneficial in several HD animal models. The drug JQ1, which inhibits histone acetyl-lysine reader bromodomains, has shown promise for multiple cancers and neurodegenerative disease. We tested whether JQ1 could improve behavioral phenotypes in the R6/2 mouse model of HD and modulate HD-associated changes in transcription and epigenomics. R6/2 and non-transgenic (NT) mice were treated with JQ1 daily from 5 to 11 weeks of age and behavioral phenotypes evaluated over this period. Following the trial, cortex and striatum were isolated and subjected to mRNA-seq and ChIP-seq for the histone marks H3K4me3 and H3K27ac. Initially, JQ1 enhanced motor performance in NT mice. In R6/2 mice, however, JQ1 had no effect on rotarod or grip strength but exacerbated weight loss and worsened performance on the pole test. JQ1-induced gene expression changes in NT mice were distinct from those in R6/2 and primarily involved protein translation and bioenergetics pathways. Dysregulation of HD-related pathways in striatum was exacerbated by JQ1 in R6/2 mice, but not in NTs, and JQ1 caused a corresponding increase in the formation of a mutant huntingtin protein-dependent high molecular weight species associated with pathogenesis. This study suggests that drugs predicted to be beneficial based on their mode of action and effects in wild-type or in other neurodegenerative disease models may have an altered impact in the HD context. These observations have important implications in the development of epigenetic modulators as therapies for HD.

Individual brain organoids reproducibly form cell diversity of the human cerebral cortex.

Experimental models of the human brain are needed for basic understanding of its development and disease1. Human brain organoids hold unprecedented promise for this purpose; however, they are plagued by high organoid-to-organoid variability2,3. This has raised doubts as to whether developmental processes of the human brain can occur outside the context of embryogenesis with a degree of reproducibility that is comparable to the endogenous tissue. Here we show that an organoid model of the dorsal forebrain can reliably generate a rich diversity of cell types appropriate for the human cerebral cortex. We performed single-cell RNA-sequencing analysis of 166,242 cells isolated from 21 individual organoids, finding that 95% of the organoids generate a virtually indistinguishable compendium of cell types, following similar developmental trajectories and with a degree of organoid-to-organoid variability comparable to that of individual endogenous brains. Furthermore, organoids derived from different stem cell lines show consistent reproducibility in the cell types produced. The data demonstrate that reproducible development of the complex cellular diversity of the central nervous system does not require the context of the embryo, and that establishment of terminal cell identity is a highly constrained process that can emerge from diverse stem cell origins and growth environments.

Individual Oligodendrocytes Show Bias for Inhibitory Axons in the Neocortex.

Reciprocal communication between neurons and oligodendrocytes is essential for the generation and localization of myelin, a critical feature of the CNS. In the neocortex, individual oligodendrocytes can myelinate multiple axons; however, the neuronal origin of the myelinated axons has remained undefined and, while largely assumed to be from excitatory pyramidal neurons, it also includes inhibitory interneurons. This raises the question of whether individual oligodendrocytes display bias for the class of neurons that they myelinate. Here, we find that different classes of cortical interneurons show distinct patterns of myelin distribution starting from the onset of myelination, suggesting that oligodendrocytes can recognize the class identity of individual types of interneurons that they target. Notably, we show that some oligodendrocytes disproportionately myelinate the axons of inhibitory interneurons, whereas others primarily target excitatory axons or show no bias. These results point toward very specific interactions between oligodendrocytes and neurons and raise the interesting question of why myelination is differentially directed toward different neuron types.

Turning omics data into therapeutic insights.

Omics technologies have made it easier and cheaper to evaluate thousands of biological molecules at once. These advances have led to novel therapies approved for use in the clinic, elucidated the mechanisms behind disease-associated mutations, led to increased accuracy in disease subtyping and personalized medicine, and revealed novel uses and treatment regimes for existing drugs through drug repurposing and pharmacology studies. In this review, we summarize some of these milestones and discuss the potential of integrative analyses that combine multiple data types for further advances.

Discovering Altered Regulation and Signaling Through Network-based Integration of Transcriptomic, Epigenomic, and Proteomic Tumor Data.

With the extraordinary rise in available biological data, biologists and clinicians need unbiased tools for data integration in order to reach accurate, succinct conclusions. Network biology provides one such method for high-throughput data integration, but comes with its own set of algorithmic problems and needed expertise. We provide a step-by-step guide for using Omics Integrator, a software package designed for the integration of transcriptomic, epigenomic, and proteomic data. Omics Integrator can be found at http://fraenkel.mit.edu/omicsintegrator .

PCSF: An R-package for network-based interpretation of high-throughput data.

With the recent technological developments a vast amount of high-throughput data has been profiled to understand the mechanism of complex diseases. The current bioinformatics challenge is to interpret the data and underlying biology, where efficient algorithms for analyzing heterogeneous high-throughput data using biological networks are becoming increasingly valuable. In this paper, we propose a software package based on the Prize-collecting Steiner Forest graph optimization approach. The PCSF package performs fast and user-friendly network analysis of high-throughput data by mapping the data onto a biological networks such as protein-protein interaction, gene-gene interaction or any other correlation or coexpression based networks. Using the interaction networks as a template, it determines high-confidence subnetworks relevant to the data, which potentially leads to predictions of functional units. It also interactively visualizes the resulting subnetwork with functional enrichment analysis.

Huntington's Disease iPSC-Derived Brain Microvascular Endothelial Cells Reveal WNT-Mediated Angiogenic and Blood-Brain Barrier Deficits.

Brain microvascular endothelial cells (BMECs) are an essential component of the blood-brain barrier (BBB) that shields the brain against toxins and immune cells. While BBB dysfunction exists in neurological disorders, including Huntington's disease (HD), it is not known if BMECs themselves are functionally compromised to promote BBB dysfunction. Further, the underlying mechanisms of BBB dysfunction remain elusive given limitations with mouse models and post-mortem tissue to identify primary deficits. We undertook a transcriptome and functional analysis of human induced pluripotent stem cell (iPSC)-derived BMECs (iBMEC) from HD patients or unaffected controls. We demonstrate that HD iBMECs have intrinsic abnormalities in angiogenesis and barrier properties, as well as in signaling pathways governing these processes. Thus, our findings provide an iPSC-derived BBB model for a neurodegenerative disease and demonstrate autonomous neurovascular deficits that may underlie HD pathology with implications for therapeutics and drug delivery.

Network-Based Interpretation of Diverse High-Throughput Datasets through the Omics Integrator Software Package.

High-throughput, 'omic' methods provide sensitive measures of biological responses to perturbations. However, inherent biases in high-throughput assays make it difficult to interpret experiments in which more than one type of data is collected. In this work, we introduce Omics Integrator, a software package that takes a variety of 'omic' data as input and identifies putative underlying molecular pathways. The approach applies advanced network optimization algorithms to a network of thousands of molecular interactions to find high-confidence, interpretable subnetworks that best explain the data. These subnetworks connect changes observed in gene expression, protein abundance or other global assays to proteins that may not have been measured in the screens due to inherent bias or noise in measurement. This approach reveals unannotated molecular pathways that would not be detectable by searching pathway databases. Omics Integrator also provides an elegant framework to incorporate not only positive data, but also negative evidence. Incorporating negative evidence allows Omics Integrator to avoid unexpressed genes and avoid being biased toward highly-studied hub proteins, except when they are strongly implicated by the data. The software is comprised of two individual tools, Garnet and Forest, that can be run together or independently to allow a user to perform advanced integration of multiple types of high-throughput data as well as create condition-specific subnetworks of protein interactions that best connect the observed changes in various datasets. It is available at http://fraenkel.mit.edu/omicsintegrator and on GitHub at https://github.com/fraenkel-lab/OmicsIntegrator.