High content image analysis identifies novel regulators of synaptogenesis in a high-throughput RNAi screen of primary neurons

Transcriptional and cellular response of hiPSC-derived microglia-neural progenitor co-cultures exposed to IL-6

Elevated interleukin (IL-)6 levels during prenatal development have been linked to increased risk for neurodevelopmental disorders (NDD) in the offspring, but the mechanism remains unclear. Human-induced pluripotent stem cell (hiPSC) models offer a valuable tool to study the effects of IL-6 on features relevant for human neurodevelopment in vitro. We previously reported that hiPSC-derived microglia-like cells (MGLs) respond to IL-6, but neural progenitor cells (NPCs) in monoculture do not. Therefore, we investigated whether co-culturing hiPSC-derived MGLs with NPCs would trigger a cellular response to IL-6 stimulation via secreted factors from the MGLs. Using N=4 donor lines without psychiatric diagnosis, we first confirmed that NPCs can respond to IL-6 through trans-signalling when recombinant IL-6Ra is present, and that this response is dose-dependent. MGLs secreted soluble IL-6R, but at lower levels than found in vivo and below that needed to activate trans-signalling in NPCs. Whilst transcriptomic and secretome analysis confirmed that MGLs undergo substantial transcriptomic changes after IL-6 exposure and subsequently secrete a cytokine milieu, NPCs in co-culture with MGLs exhibited a minimal transcriptional response. Furthermore, there were no significant cell fate-acquisition changes when differentiated into post-mitotic cultures, nor alterations in synaptic densities in mature neurons. These findings highlight the need to investigate if trans-IL-6 signalling to NPCs is a relevant disease mechanism linking prenatal IL-6 exposure to increased risk for psychiatric disorders. Moreover, our findings underscore the importance of establishing more complex in vitro human models with diverse cell types, which may show cell-specific responses to microglia-released cytokines to fully understand how IL-6 exposure may influence human neurodevelopment.

Disease phenotypic screening in neuron-glia cocultures identifies blockers of inflammatory neurodegeneration

Neuropathology is often mediated by interactions between neurons and glia that cannot be modeled by monocultures. However, cocultures are difficult to use and analyze for high-content screening. Here, we perform compound screening using primary neuron-glia cultures to model inflammatory neurodegeneration, live-cell stains, and automated classification of neurons, astrocytes or microglia using open-source software. Out of 227 compounds with known bioactivities, 29 protected against lipopolysaccharide-induced neuronal loss, including drugs affecting adrenergic, steroid, inflammatory and MAP kinase signaling. The screen also identified physiological compounds, such as noradrenaline and progesterone, that protected and identified neurotoxic compounds, such as a TLR7 agonist, that induced microglial proliferation. Most compounds used here have not been tested in a neuron-glia coculture neurodegeneration assay previously. Thus, combining a complex cellular disease model with high-content screening of known compounds and automated image analysis allows identification of important biology, as well as potential targets and drugs for treatment.

High-Content Screening of Synaptic Density Modulators in Primary Neuronal Cultures

The synapse, which represents the structural and functional basis of neuronal communication, is one of the first elements affected in several neurodegenerative diseases. To better understand the potential role of gene expression in synapse loss, we developed an original high-content screening (HCS) model capable of quantitatively assessing the impact of gene silencing on synaptic density. Our approach is based on a model of primary neuronal cultures (PNCs) from the neonatal rat hippocampus, whose mature synapses are visualized by the relative localization of the presynaptic protein Synaptophysin with the postsynaptic protein Homer1. The heterogeneity of PNCs and the small sizes of the synaptic structures pose technical challenges associated with the level of automation necessary for HCS studies. We overcame these technical challenges, automated the processes of image analysis and data analysis, and carried out tests under real-world conditions to demonstrate the robustness of the model developed. In this article, we describe the screening of a custom library of 198 shRNAs in PNCs in the 384-well plate format. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Culture of primary hippocampal rat neurons in 384-well plates Basic Protocol 2: Lentiviral shRNA transduction of primary neuronal culture in 384-well plates Basic Protocol 3: Immunostaining of the neuronal network and synaptic markers in 384-well plates Basic Protocol 4: Image acquisition using a high-throughput reader Basic Protocol 5: Image segmentation and analysis Basic Protocol 6: Synaptic density analysis.

High-content synaptic phenotyping in human cellular models reveals a role for BET proteins in synapse assembly

Resolving fundamental molecular and functional processes underlying human synaptic development is crucial for understanding normal brain function as well as dysfunction in disease. Based upon increasing evidence of species-divergent features of brain cell types, coupled with emerging studies of complex human disease genetics, we developed the first automated and quantitative high-content synaptic phenotyping platform using human neurons and astrocytes. To establish the robustness of our platform, we screened the effects of 376 small molecules on presynaptic density, neurite outgrowth, and cell viability, validating six small molecules that specifically enhanced human presynaptic density in vitro. Astrocytes were essential for mediating the effects of all six small molecules, underscoring the relevance of non-cell-autonomous factors in synapse assembly and their importance in synaptic screening applications. Bromodomain and extraterminal (BET) inhibitors emerged as the most prominent hit class and global transcriptional analyses using multiple BET inhibitors confirmed upregulation of synaptic gene expression. Through these analyses, we demonstrate the robustness of our automated screening platform for identifying potent synaptic modulators, which can be further leveraged for scaled analyses of human synaptic mechanisms and drug discovery efforts.

Identification of the common neurobiological process disturbed in genetic and non-genetic models for autism spectrum disorders

Autism spectrum disorders (ASD) are neurodevelopmental disorders. Genetic factors, along with non-genetic triggers, have been shown to play a causative role. Despite the various causes, a triad of common symptoms defines individuals with ASD; pervasive social impairments, impaired social communication, and repeated sensory-motor behaviors. Therefore, it can be hypothesized that different genetic and environmental factors converge on a single hypothetical neurobiological process that determines these behaviors. However, the cellular and subcellular signature of this process is, so far, not well understood. Here, we performed a comparative study using "omics" approaches to identify altered proteins and, thereby, biological processes affected in ASD. In this study, we mined publicly available repositories for genetic mouse model data sets, identifying six that were suitable, and compared them with in-house derived proteomics data from prenatal zinc (Zn)-deficient mice, a non-genetic mouse model with ASD-like behavior. Findings derived from these comparisons were further validated using in vitro neuronal cell culture models for ASD. We could show that a protein network, centered on VAMP2, STX1A, RAB3A, CPLX2, and AKAP5, is a key convergence point mediating synaptic vesicle release and recycling, a process affected across all analyzed models. Moreover, we demonstrated that Zn availability has predictable functional effects on synaptic vesicle release in line with the alteration of proteins in this network. In addition, drugs that target kinases, reported to regulate key proteins in this network, similarly impacted the proteins' levels and distribution. We conclude that altered synaptic stability and plasticity through abnormal synaptic vesicle dynamics and function may be the common neurobiological denominator of the shared behavioral abnormalities in ASD and, therefore, a prime drug target for developing therapeutic strategies.

High-throughput Analysis of Synaptic Activity in Electrically Stimulated Neuronal Cultures

Synaptic dysfunction is a hallmark of various neurodegenerative and neurodevelopmental disorders. To interrogate synapse function in a systematic manner, we have established an automated high-throughput imaging pipeline based on fluorescence microscopy acquisition and image analysis of electrically stimulated synaptic transmission in neuronal cultures. Identification and measurement of synaptic signal fluctuations is achieved by means of an image analysis algorithm based on singular value decomposition. By exploiting the synchronicity of the evoked responses, the algorithm allows disentangling distinct temporally correlated patterns of firing synapse populations or cell types that are present in the same recording. We demonstrate the performance of the analysis with a pilot compound screen and show that the multiparametric readout allows classifying treatments by their spatiotemporal fingerprint. The image analysis and visualization software has been made publicly available on Github ( https://www.github.com/S3Toolbox ). The streamlined automation of multi-well image acquisition, electrical stimulation, analysis, and meta-data warehousing facilitates large-scale synapse-oriented screens and, in doing so, it will accelerate the drug discovery process.

Cellular Models and High-Throughput Screening for Genetic Causality of Intellectual Disability

Intellectual disabilities (ID) are a type of neurodevelopmental disorder (NDD). They can have a genetic cause, including an emerging class of ID centring around Rho GTPases, such as Ras-related C3 botulinum toxin substrate 1 (RAC1). Guidelines for establishing genetic causality include the use of cellular models, which often have morphological aberrations, a long-standing hallmark of ID. Disease cellular models can facilitate high-throughput screening (HTS) of chemical or genetic perturbations, which can provide translatable biological insight. Here, we discuss a class of IDs centring around RAC1. We review novel and established cellular models of ID, including mouse and human primary cells and reprogrammed or induced neurons. Finally, we review progress and remaining challenges in the adoption of HTS methodologies by the community studying neurological disorders.

Systematic Quantification of Synapses in Primary Neuronal Culture

Most neurological disorders display impaired synaptic connectivity. Hence, modulation of synapse formation may have therapeutic relevance. However, the high density and small size of synapses complicate their quantification. To improve synapse-oriented screens, we analyzed the labeling performance of synapse-targeting antibodies on neuronal cell cultures using segmentation-independent image analysis based on sliding window correlation. When assessing pairwise colocalization, a common readout for mature synapses, overlap was incomplete and confounded by spurious signals. To circumvent this, we implemented a proximity ligation-based approach that only leads to a signal when two markers are sufficiently close. We applied this approach to different marker combinations and demonstrate its utility for detecting synapse density changes in healthy and compromised cultures. Thus, segmentation-independent analysis and exploitation of resident protein proximity increases the sensitivity of synapse quantifications in neuronal cultures and represents a valuable extension to the analytical toolset for in vitro synapse screens.

Bryostatin 1 Promotes Synaptogenesis and Reduces Dendritic Spine Density in Cortical Cultures through a PKC-Dependent Mechanism

The marine natural product bryostatin 1 has demonstrated procognitive and antidepressant effects in animals and has been entered into human clinical trials for treating Alzheimer's disease (AD). The ability of bryostatin 1 to enhance learning and memory has largely been attributed to its effects on the structure and function of hippocampal neurons. However, relatively little is known about how bryostatin 1 influences the morphology of cortical neurons, key cells that also support learning and memory processes and are negatively impacted in AD. Here, we use a combination of carefully designed chemical probes and pharmacological inhibitors to establish that bryostatin 1 increases cortical synaptogenesis while decreasing dendritic spine density in a protein kinase C (PKC)-dependent manner. The effects of bryostatin 1 on cortical neurons are distinct from those induced by neural plasticity-promoting psychoplastogens such as ketamine. Compounds capable of increasing synaptic density with concomitant loss of immature dendritic spines may represent a unique pharmacological strategy for enhancing memory by improving signal-to-noise ratio in the central nervous system.

Live Neuron High-Content Screening Reveals Synaptotoxic Activity in Alzheimer Mouse Model Homogenates

Accurate quantification of synaptic changes is essential for understanding the molecular mechanisms of synaptogenesis, synaptic plasticity, and synaptic toxicity. Here we demonstrate a robust high-content imaging method for the assessment of synaptic changes and apply the method to brain homogenates from an Alzheimer's disease mouse model. Our method uses serial imaging of endogenous fluorescent labeled presynaptic VAMP2 and postsynaptic PSD95 in long-term cultured live primary neurons in 96 well microplates, and uses automatic image analysis to quantify the number of colocalized mature synaptic puncta for the assessment of synaptic changes in live neurons. As a control, we demonstrated that our synaptic puncta assay is at least 10-fold more sensitive to the toxic effects of glutamate than the MTT assay. Using our assay, we have compared synaptotoxic activities in size-exclusion chromatography fractioned protein samples from 3xTg-AD mouse model brain homogenates. Multiple synaptotoxic activities were found in high and low molecular weight fractions. Amyloid-beta immunodepletion alleviated some but not all of the synaptotoxic activities. Although the biochemical entities responsible for the synaptotoxic activities have yet to be determined, these proof-of-concept results demonstrate that this novel assay may have many potential mechanistic and therapeutic applications.

Automated Live-Cell Imaging of Synapses in Rat and Human Neuronal Cultures

Synapse loss and dendritic damage correlate with cognitive decline in many neurodegenerative diseases, underlie neurodevelopmental disorders, and are associated with environmental and drug-induced CNS toxicities. However, screening assays designed to measure loss of synaptic connections between live cells are lacking. Here, we describe the design and validation of automated synaptic imaging assay (ASIA), an efficient approach to label, image, and analyze synapses between live neurons. Using viral transduction to express fluorescent proteins that label synapses and an automated computer-controlled microscope, we developed a method to identify agents that regulate synapse number. ASIA is compatible with both confocal and wide-field microscopy; wide-field image acquisition is faster but requires a deconvolution step in the analysis. Both types of images feed into batch processing analysis software that can be run on ImageJ, CellProfiler, and MetaMorph platforms. Primary analysis endpoints are the number of structural synapses and cell viability. Thus, overt cell death is differentiated from subtle changes in synapse density, an important distinction when studying neurodegenerative processes. In rat hippocampal cultures treated for 24 h with 100 μM 2-bromopalmitic acid (2-BP), a compound that prevents clustering of postsynaptic density 95 (PSD95), ASIA reliably detected loss of postsynaptic density 95-enhanced green fluorescent protein (PSD95-eGFP)-labeled synapses in the absence of cell death. In contrast, treatment with 100 μM glutamate produced synapse loss and significant cell death, determined from morphological changes in a binary image created from co-expressed mCherry. Treatment with 3 mM lithium for 24 h significantly increased the number of fluorescent puncta, showing that ASIA also detects synaptogenesis. Proof of concept studies show that cell-specific promoters enable the selective study of inhibitory or principal neurons and that alternative reporter constructs enable quantification of GABAergic or glutamatergic synapses. ASIA can also be used to study synapse loss between human induced pluripotent stem cell (iPSC)-derived cortical neurons. Significant synapse loss in the absence of cell death was detected in the iPSC-derived neuronal cultures treated with either 100 μM 2-BP or 100 μM glutamate for 24 h, while 300 μM glutamate produced synapse loss and cell death. ASIA shows promise for identifying agents that evoke synaptic toxicities and screening for compounds that prevent or reverse synapse loss.

Multiplexed and high-throughput neuronal fluorescence imaging with diffusible probes

Synapses contain hundreds of distinct proteins whose heterogeneous expression levels are determinants of synaptic plasticity and signal transmission relevant to a range of diseases. Here, we use diffusible nucleic acid imaging probes to profile neuronal synapses using multiplexed confocal and super-resolution microscopy. Confocal imaging is performed using high-affinity locked nucleic acid imaging probes that stably yet reversibly bind to oligonucleotides conjugated to antibodies and peptides. Super-resolution PAINT imaging of the same targets is performed using low-affinity DNA imaging probes to resolve nanometer-scale synaptic protein organization across nine distinct protein targets. Our approach enables the quantitative analysis of thousands of synapses in neuronal culture to identify putative synaptic sub-types and co-localization patterns from one dozen proteins. Application to characterize synaptic reorganization following neuronal activity blockade reveals coordinated upregulation of the post-synaptic proteins PSD-95, SHANK3 and Homer-1b/c, as well as increased correlation between synaptic markers in the active and synaptic vesicle zones.

CRISPR Interference-Based Platform for Multimodal Genetic Screens in Human iPSC-Derived Neurons

CRISPR/Cas9-based functional genomics have transformed our ability to elucidate mammalian cell biology. However, most previous CRISPR-based screens were conducted in cancer cell lines rather than healthy, differentiated cells. Here, we describe a CRISPR interference (CRISPRi)-based platform for genetic screens in human neurons derived from induced pluripotent stem cells (iPSCs). We demonstrate robust and durable knockdown of endogenous genes in such neurons and present results from three complementary genetic screens. First, a survival-based screen revealed neuron-specific essential genes and genes that improved neuronal survival upon knockdown. Second, a screen with a single-cell transcriptomic readout uncovered several examples of genes whose knockdown had strikingly cell-type-specific consequences. Third, a longitudinal imaging screen detected distinct consequences of gene knockdown on neuronal morphology. Our results highlight the power of unbiased genetic screens in iPSC-derived differentiated cell types and provide a platform for systematic interrogation of normal and disease states of neurons. VIDEO ABSTRACT.

High-throughput microscopy exposes a pharmacological window in which dual leucine zipper kinase inhibition preserves neuronal network connectivity

Therapeutic developments for neurodegenerative disorders are redirecting their focus to the mechanisms that contribute to neuronal connectivity and the loss thereof. Using a high-throughput microscopy pipeline that integrates morphological and functional measurements, we found that inhibition of dual leucine zipper kinase (DLK) increased neuronal connectivity in primary cortical cultures. This neuroprotective effect was not only observed in basal conditions but also in cultures depleted from antioxidants and in cultures in which microtubule stability was genetically perturbed. Based on the morphofunctional connectivity signature, we further showed that the effects were limited to a specific dose and time range. Thus, our results illustrate that profiling microscopy images with deep coverage enables sensitive interrogation of neuronal connectivity and allows exposing a pharmacological window for targeted treatments. In doing so, we revealed a broad-spectrum neuroprotective effect of DLK inhibition, which may have relevance to pathological conditions that ar.e associated with compromised neuronal connectivity.

Human-Derived Brain Models: Windows into Neuropsychiatric Disorders and Drug Therapies

Human-derived neurons and brain organoids have revolutionized our ability to model brain development in a dish. In this review, we discuss the potential for human brain models to advance drug discovery for complex neuropsychiatric disorders. First, we address the advantages of human brain models to screen for new drugs capable of altering CNS activity. Next, we propose an experimental pipeline for using human-derived neurons and brain organoids to rapidly assess drug impact on key events in brain development, including neurite extension, synapse formation, and neural activity. The experimental pipeline begins with automated high content imaging for analysis of neurites, synapses, and neuronal viability. Following morphological examination, multi-well microelectrode array technology examines neural activity in response to drug treatment. These techniques can be combined with high throughput sequencing and mass spectrometry to assess associated transcriptional and proteomic changes. These combined technologies provide a foundation for neuropsychiatric drug discovery and future clinical assessment of patient-specific drug responses.

DoGNet: A deep architecture for synapse detection in multiplexed fluorescence images

Neuronal synapses transmit electrochemical signals between cells through the coordinated action of presynaptic vesicles, ion channels, scaffolding and adapter proteins, and membrane receptors. In situ structural characterization of numerous synaptic proteins simultaneously through multiplexed imaging facilitates a bottom-up approach to synapse classification and phenotypic description. Objective automation of efficient and reliable synapse detection within these datasets is essential for the high-throughput investigation of synaptic features. Convolutional neural networks can solve this generalized problem of synapse detection, however, these architectures require large numbers of training examples to optimize their thousands of parameters. We propose DoGNet, a neural network architecture that closes the gap between classical computer vision blob detectors, such as Difference of Gaussians (DoG) filters, and modern convolutional networks. DoGNet is optimized to analyze highly multiplexed microscopy data. Its small number of training parameters allows DoGNet to be trained with few examples, which facilitates its application to new datasets without overfitting. We evaluate the method on multiplexed fluorescence imaging data from both primary mouse neuronal cultures and mouse cortex tissue slices. We show that DoGNet outperforms convolutional networks with a low-to-moderate number of training examples, and DoGNet is efficiently transferred between datasets collected from separate research groups. DoGNet synapse localizations can then be used to guide the segmentation of individual synaptic protein locations and spatial extents, revealing their spatial organization and relative abundances within individual synapses. The source code is publicly available: https://github.com/kulikovv/dognet.

Image-Based Profiling of Synaptic Connectivity in Primary Neuronal Cell Culture

Neurological disorders display a broad spectrum of clinical manifestations. Yet, at the cellular level, virtually all these diseases converge into a common phenotype of dysregulated synaptic connectivity. In dementia, synapse dysfunction precedes neurodegeneration and cognitive impairment by several years, making the synapse a crucial entry point for the development of diagnostic and therapeutic strategies. Whereas high-resolution imaging and biochemical fractionations yield detailed insight into the molecular composition of the synapse, standardized assays are required to quickly gauge synaptic connectivity across large populations of cells under a variety of experimental conditions. Such screening capabilities have now become widely accessible with the advent of high-throughput, high-content microscopy. In this review, we discuss how microscopy-based approaches can be used to extract quantitative information about synaptic connectivity in primary neurons with deep coverage. We elaborate on microscopic readouts that may serve as a proxy for morphofunctional connectivity and we critically analyze their merits and limitations. Finally, we allude to the potential of alternative culture paradigms and integrative approaches to enable comprehensive profiling of synaptic connectivity.

Using High-Throughput Animal or Cell-Based Models to Functionally Characterize GWAS Signals

PURPOSE OF REVIEW

The advent of genome-wide association studies (GWASs) constituted a breakthrough in our understanding of the genetic architecture of multifactorial diseases. For Alzheimer's disease (AD), more than 20 risk loci have been identified. However, we are now facing three new challenges: (i) identifying the functional SNP or SNPs in each locus, (ii) identifying the causal gene(s) in each locus, and (iii) understanding these genes' contribution to pathogenesis.

RECENT FINDINGS

To address these issues and thus functionally characterize GWAS signals, a number of high-throughput strategies have been implemented in cell-based and whole-animal models. Here, we review high-throughput screening, high-content screening, and the use of the Drosophila model (primarily with reference to AD).

SUMMARY

We describe how these strategies have been successfully used to functionally characterize the genes in GWAS-defined risk loci. In the future, these strategies should help to translate GWAS data into knowledge and treatments.

High-Throughput Screening Raman Spectroscopy Platform for Label-Free Cellomics

We present a high-throughput screening Raman spectroscopy (HTS-RS) platform for a rapid and label-free macromolecular fingerprinting of tens of thousands eukaryotic cells. The newly proposed label-free HTS-RS platform combines automated imaging microscopy with Raman spectroscopy to enable a rapid label-free screening of cells and can be applied to a large number of biomedical and clinical applications. The potential of the new approach is illustrated by two applications. (1) HTS-RS-based differential white blood cell count. A classification model was trained using Raman spectra of 52 218 lymphocytes, 48 220 neutrophils, and 7 294 monocytes from four volunteers. The model was applied to determine a WBC differential for two volunteers and three patients, producing comparable results between HTS-RS and machine counting. (2) HTS-RS-based identification of circulating tumor cells (CTCs) in 1:1, 1:9, and 1:99 mixtures of Panc1 cells and leukocytes yielded ratios of 55:45, 10:90, and 3:97, respectively. Because the newly developed HTS-RS platform can be transferred to many existing Raman devices in all laboratories, the proposed implementation will lead to a significant expansion of Raman spectroscopy as a standard tool in biomedical cell research and clinical diagnostics.

Improved Scalability of Neuron-Based Phenotypic Screening Assays for Therapeutic Discovery in Neuropsychiatric Disorders

There is a pressing need to improve approaches for drug discovery related to neuropsychiatric disorders (NSDs). Therapeutic discovery in neuropsychiatric disorders would benefit from screening assays that can measure changes in complex phenotypes linked to disease mechanisms. However, traditional assays that track complex neuronal phenotypes, such as neuronal connectivity, exhibit poor scalability and are not compatible with high-throughput screening (HTS) procedures. Therefore, we created a neuronal phenotypic assay platform that focused on improving the scalability and affordability of neuron-based assays capable of tracking disease-relevant phenotypes. First, using inexpensive laboratory-level automation, we industrialized primary neuronal culture production, which enabled the creation of scalable assays within functioning neural networks. We then developed a panel of phenotypic assays based on culturing of primary neurons from genetically modified mice expressing HTS-compatible reporters that capture disease-relevant phenotypes. We demonstrated that a library of 1,280 compounds was quickly screened against both assays using only a few litters of mice in a typical academic laboratory setting. Finally, we implemented one assay in a fully automated high-throughput academic screening facility, illustrating the scalability of assays designed using this platform. These methodological improvements simplify the creation of highly scalable neuron-based phenotypic assays designed to improve drug discovery in CNS disorders.

Myostatin-like proteins regulate synaptic function and neuronal morphology

Growth factors of the TGFβ superfamily play key roles in regulating neuronal and muscle function. Myostatin (or GDF8) and GDF11 are potent negative regulators of skeletal muscle mass. However, expression of myostatin and its cognate receptors in other tissues, including brain and peripheral nerves, suggests a potential wider biological role. Here, we show that Myoglianin (MYO), the Drosophila homolog of myostatin and GDF11, regulates not only body weight and muscle size, but also inhibits neuromuscular synapse strength and composition in a Smad2-dependent manner. Both myostatin and GDF11 affected synapse formation in isolated rat cortical neuron cultures, suggesting an effect on synaptogenesis beyond neuromuscular junctions. We also show that MYO acts in vivo to inhibit synaptic transmission between neurons in the escape response neural circuit of adult flies. Thus, these anti-myogenic proteins act as important inhibitors of synapse function and neuronal growth.

Summary: Myostatin-like proteins can modulate neuromuscular synapse strength as well as synaptogenesis beyond neuromuscular junctions, highlighting a key role for these proteins in synapse function and neuronal growth.

High content analysis in amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a devastating disease characterized by the progressive loss of motor neurons. Neurons, astrocytes, oligodendrocytes and microglial cells all undergo pathological modifications in the onset and progression of ALS. A number of genes involved in the etiopathology of the disease have been identified, but a complete understanding of the molecular mechanisms of ALS has yet to be determined. Currently, people affected by ALS have a life expectancy of only two to five years from diagnosis. The search for a treatment has been slow and mostly unsuccessful, leaving patients in desperate need of better therapies. Until recently, most pre-clinical studies utilized the available ALS animal models. In the past years, the development of new protocols for isolation of patient cells and differentiation into relevant cell types has provided new tools to model ALS, potentially more relevant to the disease itself as they directly come from patients. The use of stem cells is showing promise to facilitate ALS research by expanding our understanding of the disease and help to identify potential new therapeutic targets and therapies to help patients. Advancements in high content analysis (HCA) have the power to contribute to move ALS research forward by combining automated image acquisition along with digital image analysis. With modern HCA machines it is possible, in a period of just a few hours, to observe changes in morphology and survival of cells, under the stimulation of hundreds, if not thousands of drugs and compounds. In this article, we will summarize the major molecular and cellular hallmarks of ALS, describe the advancements provided by the in vitro models developed in the last few years, and review the studies that have applied HCA to the ALS field to date.

Phenotypic screening with primary neurons to identify drug targets for regeneration and degeneration

High-throughput, target-based screening techniques have been utilized extensively for drug discovery in the past several decades. However, the need for more predictive in vitro models of in vivo disease states has generated a shift in strategy towards phenotype-based screens. Phenotype based screens are particularly valuable in studying complex conditions such as CNS injury and degenerative disease, as many factors can contribute to a specific cellular response. In this review, we will discuss different screening frameworks and their relative utility in examining mechanisms of neurodegeneration and axon regrowth, particularly in cell-based in vitro disease models.

The application of CRISPR technology to high content screening in primary neurons

Axon growth is coordinated by multiple interacting proteins that remain incompletely characterized. High content screening (HCS), in which manipulation of candidate genes is combined with rapid image analysis of phenotypic effects, has emerged as a powerful technique to identify key regulators of axon outgrowth. Here we explore the utility of a genome editing approach referred to as CRISPR (Clustered Regularly Interspersed Palindromic Repeats) for knockout screening in primary neurons. In the CRISPR approach a DNA-cleaving Cas enzyme is guided to genomic target sequences by user-created guide RNA (sgRNA), where it initiates a double-stranded break that ultimately results in frameshift mutation and loss of protein production. Using electroporation of plasmid DNA that co-expresses Cas9 enzyme and sgRNA, we first verified the ability of CRISPR targeting to achieve protein-level knockdown in cultured postnatal cortical neurons. Targeted proteins included NeuN (RbFox3) and PTEN, a well-studied regulator of axon growth. Effective knockdown lagged at least four days behind transfection, but targeted proteins were eventually undetectable by immunohistochemistry in >80% of transfected cells. Consistent with this, anti-PTEN sgRNA produced no changes in neurite outgrowth when assessed three days post-transfection. When week-long cultures were replated, however, PTEN knockdown consistently increased neurite lengths. These CRISPR-mediated PTEN effects were achieved using multi-well transfection and automated phenotypic analysis, indicating the suitability of PTEN as a positive control for future CRISPR-based screening efforts. Combined, these data establish an example of CRISPR-mediated protein knockdown in primary cortical neurons and its compatibility with HCS workflows.

Improved detection of soma location and morphology in fluorescence microscopy images of neurons

BACKGROUND

Automated detection and segmentation of somas in fluorescent images of neurons is a major goal in quantitative studies of neuronal networks, including applications of high-content-screenings where it is required to quantify multiple morphological properties of neurons. Despite recent advances in image processing targeted to neurobiological applications, existing algorithms of soma detection are often unreliable, especially when processing fluorescence image stacks of neuronal cultures.

NEW METHOD

In this paper, we introduce an innovative algorithm for the detection and extraction of somas in fluorescent images of networks of cultured neurons where somas and other structures exist in the same fluorescent channel. Our method relies on a new geometrical descriptor called Directional Ratio and a collection of multiscale orientable filters to quantify the level of local isotropy in an image. To optimize the application of this approach, we introduce a new construction of multiscale anisotropic filters that is implemented by separable convolution.

RESULTS

Extensive numerical experiments using 2D and 3D confocal images show that our automated algorithm reliably detects somas, accurately segments them, and separates contiguous ones.

COMPARISON WITH EXISTING METHODS

We include a detailed comparison with state-of-the-art existing methods to demonstrate that our algorithm is extremely competitive in terms of accuracy, reliability and computational efficiency.

CONCLUSIONS

Our algorithm will facilitate the development of automated platforms for high content neuron image processing. A Matlab code is released open-source and freely available to the scientific community.

Colocalization of synapse marker proteins evaluated by STED-microscopy reveals patterns of neuronal synapse distribution in vitro

BACKGROUND

Quantification of synapses and their morphological analysis are extensively used in network development and connectivity studies, drug screening and other areas of neuroscience. Thus, a number of quantitative approaches were introduced so far. However, most of the available methods are highly tailored to specific applications and have limitations for widespread use.

NEW METHOD

We present a new plugin for the open-source software ImageJ to provide a modifiable, high-throughput and easy to use method for synaptic puncta analysis. Our approach is based on colocalization of pre- and postsynaptic protein markers. Structurally completed glutamatergic and GABAergic synapses were identified by VGLUT1-PSD95 and VGAT-gephyrin colocalization, respectively. By combining conventional confocal microscopy with stimulated emission depletion (STED) imaging, we propose a method to quantify the number of scaffolding protein clusters, recruited to a single postsynaptic density.

RESULTS

In a proof-of-concept study, we reveal the differential distribution of glutamatergic and GABAergic synapse density with reference to perineuronal net (PNN) expression. Using super-resolution STED imaging, we demonstrate that postsynaptic puncta of completed synapses are composed of significantly more protein clusters, compared to uncompleted synapses.

COMPARISON WITH EXISTING METHODS

Our Synapse Counter plugin for ImageJ offers a rapid and unbiased research tool for a broad spectrum of neuroscientists. The proposed method of synaptic protein clusters quantification exploits super-resolution imaging to provide a comprehensive approach to the analysis of postsynaptic density composition.

CONCLUSIONS

Our results strongly substantiate the benefits of colocalization-based synapse detection.

Neural Circuits on a Chip

Neural circuits are responsible for the brain's ability to process and store information. Reductionist approaches to understanding the brain include isolation of individual neurons for detailed characterization. When maintained in vitro for several days or weeks, dissociated neurons self-assemble into randomly connected networks that produce synchronized activity and are capable of learning. This review focuses on efforts to control neuronal connectivity in vitro and construct living neural circuits of increasing complexity and precision. Microfabrication-based methods have been developed to guide network self-assembly, accomplishing control over in vitro circuit size and connectivity. The ability to control neural connectivity and synchronized activity led to the implementation of logic functions using living neurons. Techniques to construct and control three-dimensional circuits have also been established. Advances in multiple electrode arrays as well as genetically encoded, optical activity sensors and transducers enabled highly specific interfaces to circuits composed of thousands of neurons. Further advances in on-chip neural circuits may lead to better understanding of the brain.

Microscopy-Based High-Content Screening

Image-based screening is used to measure a variety of phenotypes in cells and whole organisms. Combined with perturbations such as RNA interference, small molecules, and mutations, such screens are a powerful method for gaining systematic insights into biological processes. Screens have been applied to study diverse processes, such as protein-localization changes, cancer cell vulnerabilities, and complex organismal phenotypes. Recently, advances in imaging and image-analysis methodologies have accelerated large-scale perturbation screens. Here, we describe the state of the art for image-based screening experiments and delineate experimental approaches and image-analysis approaches as well as discussing challenges and future directions, including leveraging CRISPR/Cas9-mediated genome engineering.

Automatic Dendritic Length Quantification for High Throughput Screening of Mature Neurons

High-throughput automated fluorescent imaging and screening are important for studying neuronal development, functions, and pathogenesis. An automatic approach of analyzing images acquired in automated fashion, and quantifying dendritic characteristics is critical for making such screens high-throughput. However, automatic and effective algorithms and tools, especially for the images of mature mammalian neurons with complex arbors, have been lacking. Here, we present algorithms and a tool for quantifying dendritic length that is fundamental for analyzing growth of neuronal network. We employ a divide-and-conquer framework that tackles the challenges of high-throughput images of neurons and enables the integration of multiple automatic algorithms. Within this framework, we developed algorithms that adapt to local properties to detect faint branches. We also developed a path search that can preserve the curvature change to accurately measure dendritic length with arbor branches and turns. In addition, we proposed an ensemble strategy of three estimation algorithms to further improve the overall efficacy. We tested our tool on images for cultured mouse hippocampal neurons immunostained with a dendritic marker for high-throughput screen. Results demonstrate the effectiveness of our proposed method when comparing the accuracy with previous methods. The software has been implemented as an ImageJ plugin and available for use.

Building a Terminal: Mechanisms of Presynaptic Development in the CNS

To create a presynaptic terminal, molecular signaling events must be orchestrated across a number of subcellular compartments. In the soma, presynaptic proteins need to be synthesized, packaged together, and attached to microtubule motors for shipment through the axon. Within the axon, transport of presynaptic packages is regulated to ensure that developing synapses receive an adequate supply of components. At individual axonal sites, extracellular interactions must be translated into intracellular signals that can incorporate mobile transport vesicles into the nascent presynaptic terminal. Even once the initial recruitment process is complete, the components and subsequent functionality of presynaptic terminals need to constantly be remodeled. Perhaps most remarkably, all of these processes need to be coordinated in space and time. In this review, we discuss how these dynamic cellular processes occur in neurons of the central nervous system in order to generate presynaptic terminals in the brain.

Axin Regulates Dendritic Spine Morphogenesis through Cdc42-Dependent Signaling

During development, scaffold proteins serve as important platforms for orchestrating signaling complexes to transduce extracellular stimuli into intracellular responses that regulate dendritic spine morphology and function. Axin (“axis inhibitor”) is a key scaffold protein in canonical Wnt signaling that interacts with specific synaptic proteins. However, the cellular functions of these protein–protein interactions in dendritic spine morphology and synaptic regulation are unclear. Here, we report that Axin protein is enriched in synaptic fractions, colocalizes with the postsynaptic marker PSD-95 in cultured hippocampal neurons, and interacts with a signaling protein Ca²⁺/calmodulin-dependent protein kinase II (CaMKII) in synaptosomal fractions. Axin depletion by shRNA in cultured neurons or intact hippocampal CA1 regions significantly reduced dendritic spine density. Intriguingly, the defective dendritic spine morphogenesis in Axin-knockdown neurons could be restored by overexpression of the small Rho-GTPase Cdc42, whose activity is regulated by CaMKII. Moreover, pharmacological stabilization of Axin resulted in increased dendritic spine number and spontaneous neurotransmission, while Axin stabilization in hippocampal neurons reduced the elimination of dendritic spines. Taken together, our findings suggest that Axin promotes dendritic spine stabilization through Cdc42-dependent cytoskeletal reorganization.

Automated detection of soma location and morphology in neuronal network cultures

Automated identification of the primary components of a neuron and extraction of its sub-cellular features are essential steps in many quantitative studies of neuronal networks. The focus of this paper is the development of an algorithm for the automated detection of the location and morphology of somas in confocal images of neuronal network cultures. This problem is motivated by applications in high-content screenings (HCS), where the extraction of multiple morphological features of neurons on large data sets is required. Existing algorithms are not very efficient when applied to the analysis of confocal image stacks of neuronal cultures. In addition to the usual difficulties associated with the processing of fluorescent images, these types of stacks contain a small number of images so that only a small number of pixels are available along the z-direction and it is challenging to apply conventional 3D filters. The algorithm we present in this paper applies a number of innovative ideas from the theory of directional multiscale representations and involves the following steps: (i) image segmentation based on support vector machines with specially designed multiscale filters; (ii) soma extraction and separation of contiguous somas, using a combination of level set method and directional multiscale filters. We also present an approach to extract the soma's surface morphology using the 3D shearlet transform. Extensive numerical experiments show that our algorithms are computationally efficient and highly accurate in segmenting the somas and separating contiguous ones. The algorithms presented in this paper will facilitate the development of a high-throughput quantitative platform for the study of neuronal networks for HCS applications.

Deep Imaging: the next frontier in microscopy

The microscope is the quintessential tool for discovery in cell biology. From its earliest incarnation as a tool to make the unseen visible, microscopes have been at the center of most revolutionizing developments in cell biology, histology and pathology. Major quantum leaps in imaging involved the dramatic improvements in resolution to see increasingly smaller structures, methods to visualize specific molecules inside of cells and tissues, and the ability to peer into living cells to study dynamics of molecules and cellular structures. The latest revolution in microscopy is Deep Imaging-the ability to look at very large numbers of samples by high-throughput microscopy at high spatial and temporal resolution. This approach is rooted in the development of fully automated high-resolution microscopes and the application of advanced computational image analysis and mining methods. Deep Imaging is enabling two novel, powerful approaches in cell biology: the ability to image thousands of samples with high optical precision allows every discernible morphological pattern to be used as a read-out in large-scale imaging-based screens, particularly in conjunction with RNAi-based screening technology; in addition, the capacity to capture large numbers of images, combined with advanced computational image analysis methods, has also opened the door to detect and analyze very rare cellular events. These two applications of Deep Imaging are revolutionizing cell biology.