GABAergic neuron dysregulation in a human neurodevelopmental model for major psychiatric disorders.

"GABA dysfunction" is a major hypothesis for the biological basis of schizophrenia with indirect supporting evidence from human post-mortem brain and genetic studies. Patient-derived induced pluripotent stem cells (iPSCs) have emerged as a valuable platform for modeling psychiatric disorders, and previous modeling has revealed glutamatergic synapse deficits. Whether GABAergic synapse properties are affected in patient-derived human neurons and how this impacts neuronal network activity remain poorly understood. Here we optimized a protocol to differentiate iPSCs into highly enriched ganglionic eminence-like neural progenitors and GABAergic neurons. Using a collection of iPSCs derived from patients of psychiatric disorders carrying a Disrupted-in-Schizophrenia 1 ( DISC1 ) mutation and their unaffected family member, together with respective isogenic lines, we identified mutation-dependent deficits in GABAergic synapse formation and function, a phenotype similar to that of mutant glutamatergic neurons. However, mutant glutamatergic and GABAergic neurons contribute differentially to neuronal network excitability and synchrony deficits. Finally, we showed that GABAergic synaptic transmission is also defective in neurons derived from several idiopathic schizophrenia patient iPSCs. Transcriptome analysis further showed some shared gene expression dysregulation, which is more prominent in DISC1 mutant neurons. Together, our study supports a functional GABAergic synaptic deficit in major psychiatric disorders.

CircNetVis: an interactive web application for visualizing interaction networks of circular RNAs.

Analyzing the interactions of circular RNAs (circRNAs) is a crucial step in understanding their functional impacts. While there are numerous visualization tools available for investigating circRNA interaction networks, these tools are typically limited to known circRNAs from specific databases. Moreover, these existing tools usually require complex installation procedures which can be time-consuming and challenging for users. There is a lack of a user-friendly web application that facilitates interactive exploration and visualization of circRNA interaction networks. CircNetVis is an interactive online web application to enhance the analysis of human/mouse circRNA interactions. The tool allows three different input formats of circRNAs including circRNA IDs from CircBase, circRNA coordinates (chromosome, start position, end position), and circRNA sequences in the FASTA format. It integrates multiple interaction networks for visualization and investigation of the interplay between circRNA, microRNAs, mRNAs and RNA binding proteins. CircNetVis also enables users to interactively explore the interactions of unknown circRNAs which are not reported from previous databases. The tool can generate interactive plots and allows users to save results as output files for offline usage. CircNetVis is implemented as a web application using R-shiny and freely available for academic use at https://www.meb.ki.se/shiny/truvu/CircNetVis/ .

In depth characterization of midbrain organoids derived from wild type iPSC lines.

The ability to model human neurological tissues in vitro has been a major hurdle to effective drug development for neurological disorders. iPSC-derived brain organoids have emerged as a compelling solution to this problem as they have the potential to relevantly model the protein expression pattern and physiology of specific brain regions. Although many protocols now exist for the production of brain organoids, few attempts have been made to do an in-depth kinetic evaluation of expression of mature regiospecific markers of brain organoids. To address this, we differentiated midbrain-specific brain organoids from iPSC-lines derived from three apparently healthy individuals using a matrix-free, bioreactor method. We monitored the expression of midbrain-specific neuronal markers from 7 to 90-days using immunofluorescence and immunohistology. The organoids were further characterized using electron microscopy and RNA-seq. In addition to serving as a potential benchmark for the future evaluation of other differentiation protocols, the markers observed in this study can be useful as control parameters to identify and evaluate the disease phenotypes in midbrain organoid derived from patient iPSC-lines with genetic neurological disorders.

Analysis of human invasive cytotrophoblasts demonstrates mosaic aneuploidy.

A total of 24 chromosome-specific fluorescence in situ hybridization probes for interphase nucleus analysis were developed to determine the chromosomal content of individual human invasive cytotrophoblasts derived from in vitro cultured assays. At least 75% of invasive cytotrophoblasts were hyperdiploid and the total number of chromosomes ranged from 47 to 61. The results also demonstrated that these hyperdiploid invasive cytotrophoblasts showed significant heterogeneity. The most copy number gains were observed for chromosomes 13, 14, 15, 19, 21, and 22 with average copy number greater than 2.3. A parallel study using primary invasive cytotrophoblasts also showed a similar trend of copy number changes. Conclusively, 24-chromosome analysis of human non-proliferating cytotrophoblasts (interphase nuclei) was achieved. Hyperdiploidy and chromosomal heterogeneity without endoduplication in invasive cytotrophoblasts may suggest a selective advantage for invasion and short lifespan during normal placental development.

Generation and characterization of NGLY1 patient-derived midbrain organoids.

NGLY1 deficiency is an ultra-rare, autosomal recessive genetic disease caused by mutations in the NGLY1 gene encoding N-glycanase one that removes N-linked glycan. Patients with pathogenic mutations in NGLY1 have complex clinical symptoms including global developmental delay, motor disorder and liver dysfunction. To better understand the disease pathogenesis and the neurological symptoms of the NGLY1 deficiency we generated and characterized midbrain organoids using patient-derived iPSCs from two patients with distinct disease-causing mutations-one homozygous for p. Q208X, the other compound heterozygous for p. L318P and p. R390P and CRISPR generated NGLY1 knockout iPSCs. We demonstrate that NGLY1 deficient midbrain organoids show altered neuronal development compared to one wild type (WT) organoid. Both neuronal (TUJ1) and astrocytic glial fibrillary acid protein markers were reduced in NGLY1 patient-derived midbrain organoids along with neurotransmitter GABA. Interestingly, staining for dopaminergic neuronal marker, tyrosine hydroxylase, revealed a significant reduction in patient iPSC derived organoids. These results provide a relevant NGLY1 disease model to investigate disease mechanisms and evaluate therapeutics for treatments of NGLY1 deficiency.

Generation of iPSC-Derived Brain Organoids for Drug Testing and Toxicological Evaluation.

The road to discover novel therapeutics for mental and neurological disorders has been severely hampered by the lack of access to relevant testing platforms. Currently, roughly 0.1% of drugs that show promise in preclinical testing make it to Phase I clinical trials, and 90% of those drugs go on to fail FDA approval. One of the reasons responsible for this low success rate is that conventional two-dimensional (2D) cell culture models are not accurate enough predictors of how drugs will work in humans. Three-dimensional (3D) brain organoids differentiated from induced pluripotent stem cells (iPSCs) to resemble specific parts of the human brain, which include architecture composition and physiology, can provide an alternative system that may lead to breakthroughs in key areas of drug testing and toxicological evaluation. Having reliable and scalable iPSC-derived brain organoid models that can much more accurately predict human drug responses will significantly increase success rate in developing treatments for brain-related disorders.

Evaluation of methods to detect circular RNAs from single-end RNA-sequencing data.

BACKGROUND: Circular RNA (circRNA), a class of RNA molecule with a loop structure, has recently attracted researchers due to its diverse biological functions and potential biomarkers of human diseases. Most of the current circRNA detection methods from RNA-sequencing (RNA-Seq) data utilize the mapping information of paired-end (PE) reads to eliminate false positives. However, much of the practical RNA-Seq data such as cross-linking immunoprecipitation sequencing (CLIP-Seq) data usually contain single-end (SE) reads. It is not clear how well these tools perform on SE RNA-Seq data. RESULTS: In this study, we present a systematic evaluation of six advanced RNA-based methods and two CLIP-Seq based methods for detecting circRNAs from SE RNA-Seq data. The performances of the methods are rigorously assessed based on precision, sensitivity, F1 score, and true discovery rate. We investigate the impacts of read length, false positive ratio, sequencing depth and PE mapping information on the performances of the methods using simulated SE RNA-Seq simulated datasets. The real datasets used in this study consist of four experimental RNA-Seq datasets with ≥100bp read length and 124 CLIP-Seq samples from 45 studies that contain mostly short-read (≤50bp) RNA-Seq data. The simulation study shows that the sensitivities of most of the methods can be improved by increasing either read length or sequencing depth, and that the levels of false positive rates significantly affect the precision of all methods. Furthermore, the PE mapping information can improve the method's precision but can not always guarantee the increase of F1 score. Overall, no method is dominant for all SE RNA-Seq data. The RNA-based methods perform better for the long-read datasets but are worse for the short-read datasets. In contrast, the CLIP-Seq based methods outperform the RNA-Seq based methods for all the short-read samples. Combining the results of these methods can significantly improve precision in the CLIP-Seq data. CONCLUSIONS: The results provide a systematic evaluation of circRNA detection methods on SE RNA-Seq data that would facilitate researchers' strategies in circRNA analysis.

CYFIP1 Dosages Exhibit Divergent Behavioral Impact via Diametric Regulation of NMDA Receptor Complex Translation in Mouse Models of Psychiatric Disorders.

BACKGROUND: Gene dosage imbalance caused by copy number variations (CNVs) is a prominent contributor to brain disorders. In particular, 15q11.2 CNV duplications and deletions have been associated with autism spectrum disorder and schizophrenia, respectively. The mechanism underlying these diametric contributions remains unclear. METHODS: We established both loss-of-function and gain-of-function mouse models of Cyfip1, one of four genes within 15q11.2 CNVs. To assess the functional consequences of altered CYFIP1 levels, we performed systematic investigations on behavioral, electrophysiological, and biochemical phenotypes in both mouse models. In addition, we utilized RNA immunoprecipitation sequencing (RIP-seq) analysis to reveal molecular targets of CYFIP1 in vivo. RESULTS: Cyfip1 loss-of-function and gain-of function mouse models exhibited distinct and shared behavioral abnormalities related to autism spectrum disorder and schizophrenia. RIP-seq analysis identified messenger RNA targets of CYFIP1 in vivo, including postsynaptic NMDA receptor (NMDAR) complex components. In addition, these mouse models showed diametric changes in levels of postsynaptic NMDAR complex components at synapses because of dysregulated protein translation, resulting in bidirectional alteration of NMDAR-mediated signaling. Importantly, pharmacological balancing of NMDAR signaling in these mouse models with diametric Cyfip1 dosages rescues behavioral abnormalities. CONCLUSIONS: CYFIP1 regulates protein translation of NMDAR and associated complex components at synapses to maintain normal synaptic functions and behaviors. Our integrated analyses provide insight into how gene dosage imbalance caused by CNVs may contribute to divergent neuropsychiatric disorders.

Circall: fast and accurate methodology for discovery of circular RNAs from paired-end RNA-sequencing data.

BACKGROUND: Circular RNA (circRNA) is an emerging class of RNA molecules attracting researchers due to its potential for serving as markers for diagnosis, prognosis, or therapeutic targets of cancer, cardiovascular, and autoimmune diseases. Current methods for detection of circRNA from RNA sequencing (RNA-seq) focus mostly on improving mapping quality of reads supporting the back-splicing junction (BSJ) of a circRNA to eliminate false positives (FPs). We show that mapping information alone often cannot predict if a BSJ-supporting read is derived from a true circRNA or not, thus increasing the rate of FP circRNAs. RESULTS: We have developed Circall, a novel circRNA detection method from RNA-seq. Circall controls the FPs using a robust multidimensional local false discovery rate method based on the length and expression of circRNAs. It is computationally highly efficient by using a quasi-mapping algorithm for fast and accurate RNA read alignments. We applied Circall on two simulated datasets and three experimental datasets of human cell-lines. The results show that Circall achieves high sensitivity and precision in the simulated data. In the experimental datasets it performs well against current leading methods. Circall is also substantially faster than the other methods, particularly for large datasets. CONCLUSIONS: With those better performances in the detection of circRNAs and in computational time, Circall facilitates the analyses of circRNAs in large numbers of samples. Circall is implemented in C++ and R, and available for use at https://www.meb.ki.se/sites/biostatwiki/circall and https://github.com/datngu/Circall.

Precocious neuronal differentiation and disrupted oxygen responses in Kabuki syndrome.

Chromatin modifiers act to coordinate gene expression changes critical to neuronal differentiation from neural stem/progenitor cells (NSPCs). Lysine-specific methyltransferase 2D (KMT2D) encodes a histone methyltransferase that promotes transcriptional activation and is frequently mutated in cancers and in the majority (>70%) of patients diagnosed with the congenital, multisystem intellectual disability disorder Kabuki syndrome 1 (KS1). Critical roles for KMT2D are established in various non-neural tissues, but the effects of KMT2D loss in brain cell development have not been described. We conducted parallel studies of proliferation, differentiation, transcription, and chromatin profiling in KMT2D-deficient human and mouse models to define KMT2D-regulated functions in neurodevelopmental contexts, including adult-born hippocampal NSPCs in vivo and in vitro. We report cell-autonomous defects in proliferation, cell cycle, and survival, accompanied by early NSPC maturation in several KMT2D-deficient model systems. Transcriptional suppression in KMT2D-deficient cells indicated strong perturbation of hypoxia-responsive metabolism pathways. Functional experiments confirmed abnormalities of cellular hypoxia responses in KMT2D-deficient neural cells and accelerated NSPC maturation in vivo. Together, our findings support a model in which loss of KMT2D function suppresses expression of oxygen-responsive gene programs important to neural progenitor maintenance, resulting in precocious neuronal differentiation in a mouse model of KS1.

Cell-level somatic mutation detection from single-cell RNA sequencing.

MOTIVATION: Both single-cell RNA sequencing (scRNA-seq) and DNA sequencing (scDNA-seq) have been applied for cell-level genomic profiling. For mutation profiling, the latter seems more natural. However, the task is highly challenging due to the limited input materials from only two copies of DNA molecules, while whole-genome amplification generates biases and other technical noises. ScRNA-seq starts with a higher input amount, so generally has better data quality. There exists various methods for mutation detection from DNA sequencing, it is not clear whether these methods work for scRNA-seq data. RESULTS: Mutation detection methods developed for either bulk-cell sequencing data or scDNA-seq data do not work well for the scRNA-seq data, as they produce substantial numbers of false positives. We develop a novel and robust statistical method-called SCmut-to identify specific cells that harbor mutations discovered in bulk-cell data. Statistically SCmut controls the false positives using the 2D local false discovery rate method. We apply SCmut to several scRNA-seq datasets. In scRNA-seq breast cancer datasets SCmut identifies a number of highly confident cell-level mutations that are recurrent in many cells and consistent in different samples. In a scRNA-seq glioblastoma dataset, we discover a recurrent cell-level mutation in the PDGFRA gene that is highly correlated with a well-known in-frame deletion in the gene. To conclude, this study contributes a novel method to discover cell-level mutation information from scRNA-seq that can facilitate investigation of cell-to-cell heterogeneity. AVAILABILITY AND IMPLEMENTATION: The source codes and bioinformatics pipeline of SCmut are available at https://github.com/nghiavtr/SCmut. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Vehicle Mode and Driving Activity Detection Based on Analyzing Sensor Data of Smartphones.

In this paper, we present a flexible combined system, namely the Vehicle mode-driving Activity Detection System (VADS), that is capable of detecting either the current vehicle mode or the current driving activity of travelers. Our proposed system is designed to be lightweight in computation and very fast in response to the changes of travelers' vehicle modes or driving events. The vehicle mode detection module is responsible for recognizing both motorized vehicles, such as cars, buses, and motorbikes, and non-motorized ones, for instance, walking, and bikes. It relies only on accelerometer data in order to minimize the energy consumption of smartphones. By contrast, the driving activity detection module uses the data collected from the accelerometer, gyroscope, and magnetometer of a smartphone to detect various driving activities, i.e., stopping, going straight, turning left, and turning right. Furthermore, we propose a method to compute the optimized data window size and the optimized overlapping ratio for each vehicle mode and each driving event from the training datasets. The experimental results show that this strategy significantly increases the overall prediction accuracy. Additionally, numerous experiments are carried out to compare the impact of different feature sets (time domain features, frequency domain features, Hjorth features) as well as the impact of various classification algorithms (Random Forest, Naïve Bayes, Decision tree J48, K Nearest Neighbor, Support Vector Machine) contributing to the prediction accuracy. Our system achieves an average accuracy of 98.33% in detecting the vehicle modes and an average accuracy of 98.95% in recognizing the driving events of motorcyclists when using the Random Forest classifier and a feature set containing time domain features, frequency domain features, and Hjorth features. Moreover, on a public dataset of HTC company in New Taipei, Taiwan, our framework obtains the overall accuracy of 97.33% that is considerably higher than that of the state-of the art.

Generation of human brain region-specific organoids using a miniaturized spinning bioreactor.

Human brain organoids, 3D self-assembled neural tissues derived from pluripotent stem cells, are important tools for studying human brain development and related disorders. Suspension cultures maintained by spinning bioreactors allow for the growth of large organoids despite the lack of vasculature, but commercially available spinning bioreactors are bulky in size and have low throughput. Here, we describe the procedures for building the miniaturized multiwell spinning bioreactor SpinΩ from 3D-printed parts and commercially available hardware. We also describe how to use SpinΩ to generate forebrain, midbrain and hypothalamus organoids from human induced pluripotent stem cells (hiPSCs). These organoids recapitulate key dynamic features of the developing human brain at the molecular, cellular and structural levels. The reduction in culture volume, increase in throughput and reproducibility achieved using our bioreactor and region-specific differentiation protocols enable quantitative modeling of brain disorders and compound testing. This protocol takes 14-84 d to complete (depending on the type of brain region-specific organoids and desired developmental stages), and organoids can be further maintained over 200 d. Competence with hiPSC culture is required for optimal results.

Using brain organoids to understand Zika virus-induced microcephaly.

Technologies to differentiate human pluripotent stem cells into three-dimensional organized structures that resemble in vivo organs are pushing the frontiers of human disease modeling and drug development. In response to the global health emergency posed by the Zika virus (ZIKV) outbreak, brain organoids engineered to mimic the developing human fetal brain have been employed to model ZIKV-induced microcephaly. Here, we discuss the advantages of brain organoids over other model systems to study development and highlight recent advances in understanding ZIKV pathophysiology and its underlying pathogenesis mechanisms. We further discuss perspectives on overcoming limitations of current organoid systems for their future use in ZIKV research.

Molecular signatures associated with ZIKV exposure in human cortical neural progenitors.

Zika virus (ZIKV) infection causes microcephaly and has been linked to other brain abnormalities. How ZIKV impairs brain development and function is unclear. Here we systematically profiled transcriptomes of human neural progenitor cells exposed to Asian ZIKVC, African ZIKVM, and dengue virus (DENV). In contrast to the robust global transcriptome changes induced by DENV, ZIKV has a more selective and larger impact on expression of genes involved in DNA replication and repair. While overall expression profiles are similar, ZIKVC, but not ZIKVM, induces upregulation of viral response genes and TP53. P53 inhibitors can block the apoptosis induced by both ZIKVC and ZIKVM in hNPCs, with higher potency against ZIKVC-induced apoptosis. Our analyses reveal virus- and strain-specific molecular signatures associated with ZIKV infection. These datasets will help to investigate ZIKV-host interactions and identify neurovirulence determinants of ZIKV.

Identification of small-molecule inhibitors of Zika virus infection and induced neural cell death via a drug repurposing screen.

In response to the current global health emergency posed by the Zika virus (ZIKV) outbreak and its link to microcephaly and other neurological conditions, we performed a drug repurposing screen of ∼6,000 compounds that included approved drugs, clinical trial drug candidates and pharmacologically active compounds; we identified compounds that either inhibit ZIKV infection or suppress infection-induced caspase-3 activity in different neural cells. A pan-caspase inhibitor, emricasan, inhibited ZIKV-induced increases in caspase-3 activity and protected human cortical neural progenitors in both monolayer and three-dimensional organoid cultures. Ten structurally unrelated inhibitors of cyclin-dependent kinases inhibited ZIKV replication. Niclosamide, a category B anthelmintic drug approved by the US Food and Drug Administration, also inhibited ZIKV replication. Finally, combination treatments using one compound from each category (neuroprotective and antiviral) further increased protection of human neural progenitors and astrocytes from ZIKV-induced cell death. Our results demonstrate the efficacy of this screening strategy and identify lead compounds for anti-ZIKV drug development.

Neural stem cells attacked by Zika virus.

The current outbreak of Zika virus-associated diseases in South America and its threat to spread to other parts of the world has emerged as a global health emergency. Insights from cell and animal models to understand how Zika virus causes severe birth defects may lead to treatments and prevention of these diseases.

Brain-Region-Specific Organoids Using Mini-bioreactors for Modeling ZIKV Exposure.

Cerebral organoids, three-dimensional cultures that model organogenesis, provide a new platform to investigate human brain development. High cost, variability, and tissue heterogeneity limit their broad applications. Here, we developed a miniaturized spinning bioreactor (SpinΩ) to generate forebrain-specific organoids from human iPSCs. These organoids recapitulate key features of human cortical development, including progenitor zone organization, neurogenesis, gene expression, and, notably, a distinct human-specific outer radial glia cell layer. We also developed protocols for midbrain and hypothalamic organoids. Finally, we employed the forebrain organoid platform to model Zika virus (ZIKV) exposure. Quantitative analyses revealed preferential, productive infection of neural progenitors with either African or Asian ZIKV strains. ZIKV infection leads to increased cell death and reduced proliferation, resulting in decreased neuronal cell-layer volume resembling microcephaly. Together, our brain-region-specific organoids and SpinΩ provide an accessible and versatile platform for modeling human brain development and disease and for compound testing, including potential ZIKV antiviral drugs.

Synaptic dysregulation in a human iPS cell model of mental disorders.

Dysregulated neurodevelopment with altered structural and functional connectivity is believed to underlie many neuropsychiatric disorders, and 'a disease of synapses' is the major hypothesis for the biological basis of schizophrenia. Although this hypothesis has gained indirect support from human post-mortem brain analyses and genetic studies, little is known about the pathophysiology of synapses in patient neurons and how susceptibility genes for mental disorders could lead to synaptic deficits in humans. Genetics of most psychiatric disorders are extremely complex due to multiple susceptibility variants with low penetrance and variable phenotypes. Rare, multiply affected, large families in which a single genetic locus is probably responsible for conferring susceptibility have proven invaluable for the study of complex disorders. Here we generated induced pluripotent stem (iPS) cells from four members of a family in which a frameshift mutation of disrupted in schizophrenia 1 (DISC1) co-segregated with major psychiatric disorders and we further produced different isogenic iPS cell lines via gene editing. We showed that mutant DISC1 causes synaptic vesicle release deficits in iPS-cell-derived forebrain neurons. Mutant DISC1 depletes wild-type DISC1 protein and, furthermore, dysregulates expression of many genes related to synapses and psychiatric disorders in human forebrain neurons. Our study reveals that a psychiatric disorder relevant mutation causes synapse deficits and transcriptional dysregulation in human neurons and our findings provide new insight into the molecular and synaptic etiopathology of psychiatric disorders.

Modeling a genetic risk for schizophrenia in iPSCs and mice reveals neural stem cell deficits associated with adherens junctions and polarity.

Defects in brain development are believed to contribute toward the onset of neuropsychiatric disorders, but identifying specific underlying mechanisms has proven difficult. Here, we took a multifaceted approach to investigate why 15q11.2 copy number variants are prominent risk factors for schizophrenia and autism. First, we show that human iPSC-derived neural progenitors carrying 15q11.2 microdeletion exhibit deficits in adherens junctions and apical polarity. This results from haploinsufficiency of CYFIP1, a gene within 15q11.2 that encodes a subunit of the WAVE complex, which regulates cytoskeletal dynamics. In developing mouse cortex, deficiency in CYFIP1 and WAVE signaling similarly affects radial glial cells, leading to their ectopic localization outside of the ventricular zone. Finally, targeted human genetic association analyses revealed an epistatic interaction between CYFIP1 and WAVE signaling mediator ACTR2 and risk for schizophrenia. Our findings provide insight into how CYFIP1 regulates neural stem cell function and may contribute to the susceptibility of neuropsychiatric disorders.