High-content analysis in neuroscience. Nat Rev Neurosci. 2008;9:779-788. [PMID: 18784656 DOI: 10.1038/nrn2492]

A deep learning dataset for sample preparation artefacts detection in multispectral high-content microscopy

High-content image-based screening is widely used in Drug Discovery and Systems Biology. However, sample preparation artefacts may significantly deteriorate the quality of image-based screening assays. While detection and circumvention of such artefacts could be addressed using modern-day machine learning and deep learning algorithms, this is widely impeded by the lack of suitable datasets. To address this, here we present a purpose-created open dataset of high-content microscopy sample preparation artefact. It consists of high-content microscopy of laboratory dust titrated on fixed cell culture specimens imaged with fluorescence filters covering the complete spectral range. To ensure this dataset is suitable for supervised machine learning tasks like image classification or segmentation we propose rule-based annotation strategies on categorical and pixel levels. We demonstrate the applicability of our dataset for deep learning by training a convolutional-neural-network-based classifier.

Distinct characteristics of microglia from neurogenic and non-neurogenic regions of the human brain in patients with Mesial Temporal Lobe Epilepsy

The study of microglia isolated from adult human brain tissue provides unique insight into the physiology of these brain immune cells and their role in adult human brain disorders. Reports of microglia in post-mortem adult human brain tissue show regional differences in microglial populations, however, these differences have not been fully explored in living microglia. In this study biopsy tissue was obtained from epileptic patients undergoing surgery and consisted of both cortical areas and neurogenic ventricular and hippocampal (Hp) areas. Microglia were concurrently isolated from both regions and compared by immunochemistry. Our initial observation was that a greater number of microglia resulted from isolation and culture of ventricular/Hp tissue than cortical tissue. This was found to be due to a greater proliferative capacity of microglia from ventricular/Hp regions compared to the cortex. Additionally, ventricular/Hp microglia had a greater proliferative response to the microglial mitogen Macrophage Colony-Stimulating Factor (M-CSF). This enhanced response was found to be associated with higher M-CSF receptor expression and higher expression of proteins involved in M-CSF signalling DAP12 and C/EBPβ. Microglia from the ventricular/Hp region also displayed higher expression of the receptor for Insulin-like Growth Factor-1, a molecule with some functional similarity to M-CSF. Compared to microglia isolated from the cortex, ventricular/Hp microglia showed increased HLA-DP, DQ, DR antigen presentation protein expression and a rounded morphology. These findings show that microglia from adult human brain neurogenic regions are more proliferative than cortical microglia and have a distinct protein expression profile. The data present a case for differential microglial phenotype and function in different regions of the adult human brain and suggest that microglia in adult neurogenic regions are "primed" to an activated state by their unique tissue environment.

Screening Biophysical Sensors and Neurite Outgrowth Actuators in Human Induced-Pluripotent-Stem-Cell-Derived Neurons

All living cells maintain a charge distribution across their cell membrane (membrane potential) by carefully controlled ion fluxes. These bioelectric signals regulate cell behavior (such as migration, proliferation, differentiation) as well as higher-level tissue and organ patterning. Thus, voltage gradients represent an important parameter for diagnostics as well as a promising target for therapeutic interventions in birth defects, injury, and cancer. However, despite much progress in cell and molecular biology, little is known about bioelectric states in human stem cells. Here, we present simple methods to simultaneously track ion dynamics, membrane voltage, cell morphology, and cell activity (pH and ROS), using fluorescent reporter dyes in living human neurons derived from induced neural stem cells (hiNSC). We developed and tested functional protocols for manipulating ion fluxes, membrane potential, and cell activity, and tracking neural responses to injury and reinnervation in vitro. Finally, using morphology sensor, we tested and quantified the ability of physiological actuators (neurotransmitters and pH) to manipulate nerve repair and reinnervation. These methods are not specific to a particular cell type and should be broadly applicable to the study of bioelectrical controls across a wide range of combinations of models and endpoints.

Single-particle combinatorial multiplexed liposome fusion mediated by DNA

Combinatorial high-throughput methodologies are central for both screening and discovery in synthetic biochemistry and biomedical sciences. They are, however, often reliant on large-scale analyses and thus limited by a long running time and excessive materials cost. We here present a single-particle combinatorial multiplexed liposome fusion mediated by DNA for parallelized multistep and non-deterministic fusion of individual subattolitre nanocontainers. We observed directly the efficient (>93%) and leakage free stochastic fusion sequences for arrays of surface-tethered target liposomes with six freely diffusing populations of cargo liposomes, each functionalized with individual lipidated single-stranded DNA and fluorescently barcoded by a distinct ratio of chromophores. The stochastic fusion resulted in a distinct permutation of fusion sequences for each autonomous nanocontainer. Real-time total internal reflection imaging allowed the direct observation of >16,000 fusions and 566 distinct fusion sequences accurately classified using machine learning. The high-density arrays of surface-tethered target nanocontainers (~42,000 containers per mm²) offers entire combinatorial multiplex screens using only picograms of material.

Preparation, construction and high-throughput automated analysis of human brain tissue microarrays for neurodegenerative disease drug development

A major challenge in the treatment of neurodegenerative disorders is the translation of effective therapies from the lab to the clinic. One approach to improve this process is the use of human brain tissue microarray (HBTMA) technology to aid in the discovery and validation of drug targets for brain disorders. In this protocol we describe a platform for the production of high-quality HBTMAs that can be used for drug target discovery and validation. We provide examples of the use of this platform and describe detailed protocols for HBTMA design, construction and use for both protein and mRNA detection. This platform requires less tissue and reagents than single-slide approaches, greatly increasing throughput and capacity, enabling samples to be compared in a more consistent way. It takes 4 d to construct a 60 core HBTMA. Immunohistochemistry and in situ hybridization take a further 2 d. Imaging of each HBTMA slide takes 15 min, with subsequent high-content analysis taking 30 min-2 h.

Human Brain Neuropharmacology: A Platform for Translational Neuroscience

Central nervous system (CNS) drug development has been plagued by a failure to translate effective therapies from the lab to the clinic. There are many potential reasons for this, including poor understanding of brain pharmacokinetic (PK) and pharmacodynamic (PD) factors, preclinical study flaws, clinical trial design issues, the complexity and variability of human brain diseases, as well as species differences. To address some of these problems, we have developed a platform for CNS drug discovery comprising: drug screening of primary adult human brain cells; human brain tissue microarray analysis of drug targets; and high-content phenotypic screening methods. In this opinion, I summarise the theoretical basis and the practical development and use of this platform in CNS drug discovery.

Effects of preterm birth induced with or without exogenous glucocorticoids on the ovine glucose-insulin axis

Antenatal exogenous glucocorticoids (ANG) are standard management for women at risk of preterm birth but are reputed to impair glucose tolerance in preterm offspring. We compared lambs born preterm (137 days gestation) following labour induced with exogenous glucocorticoids (G-Prem, glucocorticoid-induced preterm group), or with a progesterone synthesis inhibitor (NG-Prem, non-glucocorticoid-induced preterm group), with term-born lambs (Term; 149 days). We assessed glucose tolerance, insulin secretion and sensitivity at 4 and 10 months n = 11-14/group) and pancreatic and hepatic gene and protein expression at 4 weeks post-term (4 weeks; n = 6/group) and 12 months (12 months; n = 12-13/group). NG-Prem had higher plasma glucose concentrations than G-Prem, but not Term, at 4 months (Mean[SEM] mM: NG-Prem = 4.1[0.1]; G-Prem = 3.4[0.1]; Term = 3.7[0.1]; p = 0.003) and 10 months (NG-Prem = 3.9[0.1]; G-Prem = 3.5[0.1]; Term = 3.7[0.1]; p = 0.01). Insulin sensitivity decreased from 4 to 10 months, in NG-Prem but not in Term (Mean[SEM] µmol·ml-1·kg-1·min-1·ng-1, 4 vs. 10 months: NG-Prem = 18.7[2.5] vs. 9.5[1.5], p < 0.01; Term: 12.1[2.8] vs. 10.4[1.5], p = 0.44). At 12 months, β-cell mass in NG-Prem was reduced by 30% vs. G-Prem (p < 0.01) and 75% vs. Term (p < 0.01) and was accompanied by an increased β-cell apoptosis: proliferation ratio at 12 months. At 12 months, pancreatic glucokinase, igf2 and insulin mRNA levels were reduced 21%-71% in NG-Prem vs. G-Prem and 42%-80% vs. Term. Hepatic glut2 mRNA levels in NG-Prem were 250% of those in G-Prem and Term. Thus, induction of preterm birth without exogenous glucocorticoids more adversely affected pancreas and liver than induction with exogenous glucocorticoids. These findings do not support that ANG lead to long-term adverse metabolic effects, but support an effect of preterm birth itself.

Linoleic acid-derived metabolites constitute the majority of oxylipins in the rat pup brain and stimulate axonal growth in primary rat cortical neuron-glia co-cultures in a sex-dependent manner

In adult rats, omega-6 linoleic acid (LA, 18:2n-6) serves as a precursor to oxidized LA metabolites (OXLAMs) known to regulate multiple signaling processes in the brain. However, little is known regarding the levels or role(s) of LA and its metabolites during brain development. To address this gap, fatty acids within various brain lipid pools, and their oxidized metabolites (oxylipins) were quantified in brains from 1-day-old male and female pups using gas chromatography and liquid chromatography coupled to tandem mass spectrometry, respectively. Primary neuron-glia co-cultures derived from postnatal day 0-1 male and female rat neocortex were exposed to vehicle (0.1% ethanol), LA, the OXLAM 13-hydroxyoctadecadienoic acid (13-HODE), or prostaglandin E2 at 10-1000 nM for 48 h to test their effects on neuronal morphology. In both male and female pups, LA accounted for 1-3% of fatty acids detected in brain phospholipids and cholesteryl esters. It was not detected in triacylglycerols, and free fatty acids. Unesterified OXLAMs constituted 47-53% of measured unesterified oxylipins in males and females (vs. ~5-7% reported in adult rat brain). Of these, 13-HODE was the most abundant, accounting for 30-33% of measured OXLAMs. Brain fatty acid and OXLAM concentrations did not differ between sexes. LA and 13-HODE significantly increased axonal outgrowth. Separate analyses of cultures derived from male versus female pups revealed that LA at 1, 50, and 1000 nM, significantly increased axonal outgrowth in female but not male cortical neurons, whereas 13-HODE at 100 nM significantly increased axonal outgrowth in male but not female cortical neurons. prostaglandin E2 did not alter neuronal outgrowth in either sex. This study demonstrates that OXLAMs constitute the majority of unesterified oxylipins in the developing rat brain despite low relative abundance of their LA precursor, and highlights a novel role of LA and 13-HODE in differentially influencing neuronal morphogenesis in the developing male and female brain.

AI-powered transmitted light microscopy for functional analysis of live cells

Transmitted light microscopy can readily visualize the morphology of living cells. Here, we introduce artificial-intelligence-powered transmitted light microscopy (AIM) for subcellular structure identification and labeling-free functional analysis of live cells. AIM provides accurate images of subcellular organelles; allows identification of cellular and functional characteristics (cell type, viability, and maturation stage); and facilitates live cell tracking and multimodality analysis of immune cells in their native form without labeling.

Automated Neuron Detection in High-Content Fluorescence Microscopy Images Using Machine Learning

The study of neuronal morphology in relation to function, and the development of effective medicines to positively impact this relationship in patients suffering from neurodegenerative diseases, increasingly involves image-based high-content screening and analysis. The first critical step toward fully automated high-content image analyses in such studies is to detect all neuronal cells and distinguish them from possible non-neuronal cells or artifacts in the images. Here we investigate the performance of well-established machine learning techniques for this purpose. These include support vector machines, random forests, k-nearest neighbors, and generalized linear model classifiers, operating on an extensive set of image features extracted using the compound hierarchy of algorithms representing morphology, and the scale-invariant feature transform. We present experiments on a dataset of rat hippocampal neurons from our own studies to find the most suitable classifier(s) and subset(s) of features in the common practical setting where there is very limited annotated data for training. The results indicate that a random forests classifier using the right feature subset ranks best for the considered task, although its performance is not statistically significantly better than some support vector machine based classification models.

Clinical Trials for Disease-Modifying Therapies in Alzheimer's Disease: A Primer, Lessons Learned, and a Blueprint for the Future

Alzheimer’s disease (AD) has no currently approved disease-modifying therapies (DMTs), and treatments to prevent, delay the onset, or slow the progression are urgently needed. A delay of 5 years if available by 2025 would decrease the total number of patients with AD by 50% in 2050. To meet the definition of DMT, an agent must produce an enduring change in the course of AD; clinical trials of DMTs have the goal of demonstrating this effect. AD drug discovery entails target identification followed by high throughput screening and lead optimization of drug-like compounds. Once an optimized agent is available and has been assessed for efficacy and toxicity in animals, it progresses through Phase I testing with healthy volunteers, Phase II learning trials to establish proof-of-mechanism and dose, and Phase III confirmatory trials to demonstrate efficacy and safety in larger populations. Phase III is followed by Food and Drug Administration review and, if appropriate, market access. Trial populations include cognitively normal at-risk participants in prevention trials, mildly impaired participants with biomarker evidence of AD in prodromal AD trials, and subjects with cognitive and functional impairment in AD dementia trials. Biomarkers are critical in trials of DMTs, assisting in participant characterization and diagnosis, target engagement and proof-of-pharmacology, demonstration of disease-modification, and monitoring side effects. Clinical trial designs include randomized, parallel group; delayed start; staggered withdrawal; and adaptive. Lessons learned from completed trials inform future trials and increase the likelihood of success.

Development and Application of High-Content Biological Screening for Modulators of NET Production

Neutrophil extracellular traps (NETs) are DNA-based antimicrobial web-like structures whose release is predominantly mediated by reactive oxygen species (ROS); their purpose is to combat infections. However, unbalanced NET production and clearance is involved in tissue injury, circulation of auto-antibodies and development of several chronic diseases. Currently, there is lack of agreement regarding the high-throughput methods available for NET investigation. This study, therefore, aimed to develop and optimize a high-content analysis (HCA) approach, which can be applied for the assay of NET production and for the screening of compounds involved in the modulation of NET release. A suitable paraformaldehyde fixation protocol was established to enable HCA of neutrophils and NETs. Bespoke and in-built bioinformatics algorithms were validated by comparison with standard low-throughput approaches for application in HCA of NETs. Subsequently, the optimized protocol was applied to high-content screening (HCS) of a pharmaceutically derived compound library to identify modulators of NETosis. Of 56 compounds assessed, 8 were identified from HCS for further characterization of their effects on NET formation as being either inducers, inhibitors or biphasic modulators. The effects of these compounds on naïve neutrophils were evaluated by using specific assays for the induction of ROS and NET production, while their modulatory activity was validated in phorbol 12-myristate 13-acetate-stimulated neutrophils. Results indicated the involvement of glutathione reductase, Src family kinases, molecular-target-of-Rapamycin, and mitogen-activated-protein-kinase pathways in NET release. The compounds and pathways identified may provide targets for novel therapeutic approaches for treating NET-associated pathologies.

In vitro assessment of chemotherapy-induced neuronal toxicity

Neurotoxicity is a major concern during drug development, and together with liver and cardio-toxicity, it is one of the main causes of clinical drug attrition. Current pre-clinical models may not sufficiently identify and predict the risk for central or peripheral nervous system toxicity. One such example is clinically dose-limiting neuropathic effects after the administration of chemotherapeutic agents. Thus, the need to establish novel in vitro tools to evaluate the risk of neurotoxicities, such as neuropathy, remains unmet in drug discovery. Though in vitro studies have been conducted using primary and immortalized cell lines, some limitations include the utility for higher throughput methodologies, method reproducibility, and species extrapolation. As a novel alternative, human induced-pluripotent stem cell (iPSC)-derived neurons appear promising for testing new drug candidates. These iPSC-derived neurons are readily available and can be manipulated as required. Here, we describe a novel approach to assess neurotoxicity caused by different classes of chemotherapeutics using kinetic monitoring of neurite dynamic changes and apoptosis in human iPSC-neurons. These studies show promising changes in neurite dynamics in response to clinical inducers of neuropathy, as well as the ability to rank-order and gather mechanistic insight into class-specific compound induced neurotoxicity. This platform can be utilized in early drug development, as part of a weight of evidence approach, to screen drug candidates, and potentially reduce clinical attrition due to neurotoxicity.

Sevoflurane decreases self-renewal capacity and causes c-Jun N-terminal kinase-mediated damage of rat fetal neural stem cells

Increasing studies have demonstrated that sevoflurane can induce neurotoxicity in the developing brains. JNK normally promotes apoptosis. It was hypothesized that sevoflurane affected the proliferation and differentiation of FNSCs and induced cell apoptosis, which caused the learning and memory deficits via JNK pathway. Sevoflurane at a concentration of 1.2% did not induce damage on the FNSCS. However, concentrations of 2.4% and 4.8% decreased the cell viability, as shown by the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay, and increased apoptosis, as shown by flow cytometry. The 5-ethynyl-2'-deoxyuridine (EdU) incorporation assay demonstrated that 4.8% sevoflurane reduced the proliferation of FNSCs. Compared with the control group, the 4.8% sevoflurane group showed a decrease in the proportion of undifferentiated FNSCs at 6-h exposure; 4.8% sevoflurane could increase the p-JNK/JNK ratio. JNK inhibition by the specific inhibitor SP600125 enhanced partially the cell viability. Cumulatively, 4.8% sevoflurane induced significant damage on FNSCs; it decreased cell proliferation and proportion of undifferentiated cells as well. JNK pathway might play a key role in the decrease in survival of FNSCs induced by an inhaled anesthetic. The present findings might raise the possibility that JNK inhibition has therapeutic potential in protecting FNSCs from the adverse effects of the inhaled anesthetic.

Meeting the Challenge: Using Cytological Profiling to Discover Chemical Probes from Traditional Chinese Medicines against Parkinson's Disease

Parkinson's disease (PD) is an incurable neurodegenerative disorder with a high prevalence rate worldwide. The fact that there are currently no proven disease-modifying treatments for PD underscores the urgency for a more comprehensive understanding of the underlying disease mechanism. Chemical probes have been proven to be powerful tools for studying biological processes. Traditional Chinese medicine (TCM) contains a huge reservoir of bioactive small molecules as potential chemical probes that may hold the key to unlocking the mystery of PD biology. The TCM-sourced chemical approach to PD biology can be advanced through the use of an emerging cytological profiling (CP) technique that allows unbiased characterization of small molecules and their cellular responses. This comprehensive technique, applied to chemical probe identification from TCM and used for studying the molecular mechanisms underlying PD, may inform future therapeutic target selection and provide a new perspective to PD drug discovery.

Development and Evaluation of a Fluorescent Antibody-Drug Conjugate for Molecular Imaging and Targeted Therapy of Pancreatic Cancer

Antibodies are widely available and cost-effective research tools in life science, and antibody conjugates are now extensively used for targeted therapy, immunohistochemical staining, or in vivo diagnostic imaging of cancer. Significant advances in site-specific antibody labeling technologies have enabled the production of highly characterized and homogenous conjugates for biomedical purposes, and some recent studies have utilized site-specific labeling to synthesize bifunctional antibody conjugates with both imaging and drug delivery properties. While these advances are important for the clinical safety and efficacy of such biologics, these techniques can also be difficult, expensive, and time-consuming. Furthermore, antibody-drug conjugates (ADCs) used for tumor treatment generally remain distinct from conjugates used for diagnosis. Thus, there exists a need to develop simple dual-labeling methods for efficient therapeutic and diagnostic evaluation of antibody conjugates in pre-clinical model systems. Here, we present a rapid and simple method utilizing commercially available reagents for synthesizing a dual-labeled fluorescent ADC. Further, we demonstrate the fluorescent ADC’s utility for simultaneous targeted therapy and molecular imaging of cancer both in vitro and in vivo. Employing non-site-specific, amine-reactive chemistry, our novel biopharmaceutical theranostic is a monoclonal antibody specific for a carcinoembryonic antigen (CEA) biomarker conjugated to both paclitaxel and a near-infrared (NIR), polyethylene glycol modified (PEGylated) fluorophore (DyLight™ 680-4xPEG). Using in vitro systems, we demonstrate that this fluorescent ADC selectively binds a CEA-positive pancreatic cancer cell line (BxPC-3) in immunofluorescent staining and flow cytometry, exhibits efficient internalization kinetics, and is cytotoxic. Model studies using a xenograft of BxPC-3 cells in athymic mice also show the fluorescent ADC’s efficacy in detecting tumors in vivo and inhibiting tumor growth more effectively than equimolar amounts of unconjugated drug. Overall, our results demonstrate that non-selective, amine-targeting chemistry is an effective dual-labeling method for synthesizing and evaluating a bifunctional fluorescent antibody-drug conjugate, allowing concurrent detection, monitoring and treatment of cancer.

Real-time high dynamic range laser scanning microscopy

In conventional confocal/multiphoton fluorescence microscopy, images are typically acquired under ideal settings and after extensive optimization of parameters for a given structure or feature, often resulting in information loss from other image attributes. To overcome the problem of selective data display, we developed a new method that extends the imaging dynamic range in optical microscopy and improves the signal-to-noise ratio. Here we demonstrate how real-time and sequential high dynamic range microscopy facilitates automated three-dimensional neural segmentation. We address reconstruction and segmentation performance on samples with different size, anatomy and complexity. Finally, in vivo real-time high dynamic range imaging is also demonstrated, making the technique particularly relevant for longitudinal imaging in the presence of physiological motion and/or for quantification of in vivo fast tracer kinetics during functional imaging.

Confocal and multiphoton fluorescence microscopy often suffers from low dynamic range. Here the authors develop a high dynamic range, laser scanning fluorescence technique by simultaneously recording different light intensity ranges. The method can be adapted to commercial systems.

High-content analysis of α-synuclein aggregation and cell death in a cellular model of Parkinson's disease

BACKGROUND

Alpha-synuclein (α-SYN) aggregates represent a key feature of Parkinson's disease, but the exact relationship between α-SYN aggregation and neurodegeneration remains incompletely understood. Therefore, the availability of a cellular assay that allows medium-throughput analysis of α-SYN-linked pathology will be of great value for studying the aggregation process and for advancing α-SYN-based therapies.

NEW METHOD

Here we describe a high-content neuronal cell assay that simultaneously measures oxidative stress-induced α-SYN aggregation and apoptosis.

RESULTS

We optimized an automated and reproducible assay to quantify both α-SYN aggregation and cell death in human SH-SY5Y neuroblastoma cells.

COMPARISON WITH EXISTING METHODS

Quantification of α-SYN aggregates in cells has typically relied on manual imaging and counting or cell-free assays, which are time consuming and do not allow a concurrent analysis of cell viability. Our high-content analysis method for quantification of α-SYN aggregation allows simultaneous measurements of multiple cell parameters at a single-cell level in a fast, objective and automated manner.

CONCLUSIONS

The presented analysis approach offers a rapid, objective and multiparametric approach for the screening of compounds and genes that might alter α-SYN aggregation and/or toxicity.

Glucocorticoid-Induced Preterm Birth and Neonatal Hyperglycemia Alter Ovine β-Cell Development

Adults born preterm are at increased risk of impaired glucose tolerance and diabetes. Late gestation fetuses exposed to high blood glucose concentration also are at increased risk of impaired glucose tolerance as adults. Preterm babies commonly become hyperglycemic and are thus exposed to high blood glucose concentration at an equivalent stage of pancreatic maturation. It is not known whether preterm birth itself, or complications of prematurity, such as hyperglycemia, alter later pancreatic function. To distinguish these, we made singleton preterm lambs hyperglycemic (HYPER) for 12 days after birth with a dextrose infusion and compared them with vehicle-treated preterm and term controls and with HYPER lambs made normoglycemic with an insulin infusion. Preterm birth reduced β-cell mass, apparent by 4 weeks after term and persisting to adulthood (12 mo), and was associated with reduced insulin secretion at 4 months (juvenile) and reduced insulin mRNA expression in adulthood. Hyperglycemia in preterm lambs further down-regulated key pancreatic gene expression in adulthood. These findings indicate that reduced β-cell mass after preterm birth may be an important factor in increased risk of diabetes after preterm birth and may be exacerbated by postnatal hyperglycemia.

High-content high-throughput assays for characterizing the viability and morphology of human iPSC-derived neuronal cultures

Abstract Development of quantitative high-throughput in vitro assays that enable assessment of viability and morphological changes in neuronal cells is an active area of investigation in drug discovery and environmental chemical safety assessment. High-content imaging is an emerging and efficient tool for generating multidimensional quantitative cellular readouts; in addition, human induced pluripotent stem cell (iPSC)-derived neurons are a promising in vitro model system that emulates both the functionality and behavior of mature neurons, and they are available in quantities sufficient for screening workflows. The goal of this study was to develop high-content imaging and analysis methods to assess multiple phenotypes in human iPSC-derived neuronal cells. Specifically, we optimized cell culture, staining, and imaging protocols in a 384-well assay format and improved laboratory workflow by designing a one-step procedure to reduce assay time and minimize cell disturbance. Phenotypic readouts include quantitative characterization of neurite outgrowth and branching, cell number and viability, as well as measures of adverse effects on mitochondrial integrity and membrane potential. To verify the robustness of the workflow, we tested a series of compounds that are established toxicants. We report concentration-response effects of selected test compounds on human iPSC-derived neuronal cells and illustrate how the proposed methods may be used for high-content high-throughput compound toxicity screening and safety evaluation of drugs and environmental chemicals.

Studying Human Brain Inflammation in Leptomeningeal and Choroid Plexus Explant Cultures

The meninges (dura, pia and arachnoid) are critical membranes encasing and protecting the brain within the skull. The leptomeninges, which comprise the arachnoid and pia, have many functions beyond brain protection including roles in neurogenesis, fibrotic scar formation and brain inflammation. Similarly, the choroid plexus plays important roles in normal brain function but is also involved in brain inflammation. We have begun studying the role of human leptomeninges and choroid plexus in brain inflammation and leptomeninges in fibrotic scar formation, using human brain derived explant cultures. To study the composition of the cells generated in these explants we undertook immunocytochemical characterisation. Cells, mainly pericytes and meningeal macrophages, emerge from leptomeningeal explants (LME's) and respond to inflammatory mediators by producing inflammatory molecules. LME-derived cells also respond to mechanical injury and cytokines, providing an in vitro human brain model of fibrotic scar formation. Choroid plexus explants (CPE's) generate epithelial cells, pericytes and microglia/macrophages. CPE-derived cells also respond to inflammatory mediators. LME and CPE explants survive and generate cells for many months in vitro and provide a remarkable opportunity to study basic mechanisms of human brain inflammation and fibrosis and to test human-active anti-inflammatory and anti-scarring treatments.

Workflow for automated quantification of cerebromicrovascular gelatinase activity

The gelatinase enzymes, matrix metalloproteinases -2 and -9, are central mediators of blood-brain barrier disruption, actively studied in experimental models of neurological disease. Staining with in situ zymography (ISZ) allows visualization of gelatinase activity directly in brain tissue sections. However, quantifying microvascular gelatinase activity from ISZ-images is challenging and time consuming, as surrounding cell types often show significant confounding activity. We describe validation and performance of a workflow for automated image analysis of cerebromicrovascular gelatinase activity, now released for open-access use. In comparison to manual analysis, the automated workflow showed superior accuracy, was faster to execute and allows for more detailed analysis of heterogeneity in the microvasculature. We further suggest recommendations for quantifying and reporting this type of activity in experimental studies, focusing on ischemic stroke.

Familial Alzheimer’s disease modelling using induced pluripotent stem cell technology

Alzheimer’s disease (AD) is a progressive neurodegenerative disease in which patients exhibit gradual loss of memory that impairs their ability to learn or carry out daily tasks. Diagnosis of AD is difficult, particularly in early stages of the disease, and largely consists of cognitive assessments, with only one in four patients being correctly diagnosed. Development of novel therapeutics for the treatment of AD has proved to be a lengthy, costly and relatively unproductive process with attrition rates of > 90%. As a result, there are no cures for AD and few treatment options available for patients. Therefore, there is a pressing need for drug discovery platforms that can accurately and reproducibly mimic the AD phenotype and be amenable to high content screening applications. Here, we discuss the use of induced pluripotent stem cells (iPSCs), which can be derived from adult cells, as a method of recapitulation of AD phenotype in vitro. We assess their potential use in high content screening assays and the barriers that exist to realising their full potential in predictive efficacy, toxicology and disease modelling. At present, a number of limitations need to be addressed before the use of iPSC technology can be fully realised in AD therapeutic applications. However, whilst the use of AD-derived iPSCs in drug discovery remains a fledgling field, it is one with immense potential that is likely to reach fruition within the next few years.

Adult human glia, pericytes and meningeal fibroblasts respond similarly to IFNy but not to TGFβ1 or M-CSF

The chemokine Interferon gamma-induced protein 10 (IP-10) and human leukocyte antigen (HLA) are widely used indicators of glial activation and neuroinflammation and are up-regulated in many brain disorders. These inflammatory mediators have been widely studied in rodent models of brain disorders, but less work has been undertaken using human brain cells. In this study we investigate the regulation of HLA and IP-10, as well as other cytokines and chemokines, in microglia, astrocytes, pericytes, and meningeal fibroblasts derived from biopsy and autopsy adult human brain, using immunocytochemistry and a Cytometric Bead Array. Interferonγ (IFNγ) increased microglial HLA expression, but contrary to data in rodents, the anti-inflammatory cytokine transforming growth factor β1 (TGFβ1) did not inhibit this increase in HLA, nor did TGFβ1 affect basal microglial HLA expression or IFNγ-induced astrocytic HLA expression. In contrast, IFNγ-induced and basal microglial HLA expression, but not IFNγ-induced astrocytic HLA expression, were strongly inhibited by macrophage colony stimulating factor (M-CSF). IFNγ also strongly induced HLA expression in pericytes and meningeal fibroblasts, which do not basally express HLA, and this induction was completely blocked by TGFβ1, but not affected by M-CSF. In contrast, TGFβ1 did not block the IFNγ-induced increase in IP-10 in pericytes and meningeal fibroblasts. These results show that IFNγ, TGFβ1 and M-CSF have species- and cell type-specific effects on human brain cells that may have implications for their roles in adult human brain inflammation.

M1 muscarinic receptor activation mediates cell death in M1-HEK293 cells

HEK293 cells have been used extensively to generate stable cell lines to study G protein-coupled receptors, such as muscarinic acetylcholine receptors (mAChRs). The activation of M1 mAChRs in various cell types in vitro has been shown to be protective. To further investigate M1 mAChR-mediated cell survival, we generated stable HEK293 cell-lines expressing the human M1 mAChR. M1 mAChRs were efficiently expressed at the cell surface and efficiently internalised within 1 h by carbachol. Carbachol also induced early signalling cascades similar to previous reports. Thus, ectopically expressed M1 receptors behaved in a similar fashion to the native receptor over short time periods of analysis. However, substantial cell death was observed in HEK293-M1 cells within 24 h after carbachol application. Death was only observed in HEK cells expressing M1 receptors and fully blocked by M1 antagonists. M1 mAChR-stimulation mediated prolonged activation of the MEK-ERK pathway and resulted in prolonged induction of the transcription factor EGR-1 (>24 h). Blockade of ERK signalling with U0126 did not reduce M1 mAChR-mediated cell-death significantly but inhibited the acute induction of EGR-1. We investigated the time-course of cell death using time-lapse microscopy and xCELLigence technology. Both revealed the M1 mAChR cytotoxicity occurs within several hours of M1 activation. The xCELLigence assay also confirmed that the ERK pathway was not involved in cell-death. Interestingly, the MEK blocker did reduce carbachol-mediated cleaved caspase 3 expression in HEK293-M1 cells. The HEK293 cell line is a widely used pharmacological tool for studying G-protein coupled receptors, including mAChRs. Our results highlight the importance of investigating the longer term fate of these cells in short term signalling studies. Identifying how and why activation of the M1 mAChR signals apoptosis in these cells may lead to a better understanding of how mAChRs regulate cell-fate decisions.

High content screening as high quality assay for biological evaluation of photosensitizers in vitro

A novel single step assay approach to screen a library of photdynamic therapy (PDT) compounds was developed. Utilizing high content analysis (HCA) technologies several robust cellular parameters were identified, which can be used to determine the phototoxic effects of porphyrin compounds which have been developed as potential anticancer agents directed against esophageal carcinoma. To demonstrate the proof of principle of this approach a small detailed study on five porphyrin based compounds was performed utilizing two relevant esophageal cancer cell lines (OE21 and SKGT-4). The measurable outputs from these early studies were then evaluated by performing a pilot screen using a set of 22 compounds. These data were evaluated and validated by performing comparative studies using a traditional colorimetric assay (MTT). The studies demonstrated that the HCS assay offers significant advantages over and above the currently used methods (directly related to the intracellular presence of the compounds by analysis of their integrated intensity and area within the cells). A high correlation was found between the high content screening (HCS) and MTT data. However, the HCS approach provides additional information that allows a better understanding of the behavior of these compounds when interacting at the cellular level. This is the first step towards an automated high-throughput screening of photosensitizer drug candidates and the beginnings of an integrated and comprehensive quantitative structure action relationship (QSAR) study for photosensitizer libraries.

M-CSF increases proliferation and phagocytosis while modulating receptor and transcription factor expression in adult human microglia

Background

Microglia are the primary immune cells of the brain whose phenotype largely depends on their surrounding micro-environment. Microglia respond to a multitude of soluble molecules produced by a variety of brain cells. Macrophage colony-stimulating factor (M-CSF) is a cytokine found in the brain whose receptor is expressed by microglia. Previous studies suggest a critical role for M-CSF in brain development and normal functioning as well as in several disease processes involving neuroinflammation.

Methods

Using biopsy tissue from patients with intractable temporal epilepsy and autopsy tissue, we cultured primary adult human microglia to investigate their response to M-CSF. Mixed glial cultures were treated with 25 ng/ml M-CSF for 96 hours. Proliferation and phagocytosis assays, and high through-put immunocytochemistry, microscopy and image analysis were performed to investigate microglial phenotype and function.

Results

We found that the phenotype of primary adult human microglia was markedly changed following exposure to M-CSF. A greater number of microglia were present in the M-CSF- treated cultures as the percentage of proliferating (BrdU and Ki67-positive) microglia was greatly increased. A number of changes in protein expression occurred following M-CSF treatment, including increased transcription factors PU.1 and C/EBPβ, increased DAP12 adaptor protein, increased M-CSF receptor (CSF-1R) and IGF-1 receptor, and reduced HLA-DP, DQ, DR antigen presentation protein. Furthermore, a distinct morphological change was observed with elongation of microglial processes. These changes in phenotype were accompanied by a functional increase in phagocytosis of Aβ_1-42 peptide.

Conclusions

We show here that the cytokine M-CSF dramatically influences the phenotype of adult human microglia. These results pave the way for future investigation of M-CSF-related targets for human therapeutic benefit.

Isolation and culture of adult human microglia within mixed glial cultures for functional experimentation and high-content analysis

Microglia are thought to be involved in diseases of the adult human brain as well as normal aging processes. While neonatal and rodent microglia are often used in studies investigating microglial function, there are important differences between rodent microglia and their adult human counterparts. Human brain tissue provides a unique and valuable tool for microglial cell and molecular biology. Routine protocols can now enable use of this culture method in many laboratories. Detailed protocols and advice for culture of human brain microglia are provided here. We demonstrate the protocol for culturing human adult microglia within a mixed glial culture and use a phagocytosis assay as an example of the functional studies possible with these cells as well as a high-content analysis method of quantification.

High-content neurite development study using optically patterned substrates

The study of neurite guidance in vitro relies on the ability to reproduce the distribution of attractive and repulsive guidance molecules normally expressed in vivo. The identification of subtle variations in the neurite response to changes in the spatial distribution of extracellular molecules can be achieved by monitoring the behavior of cells on protein gradients. To do this, automated high-content screening assays are needed to quantify the morphological changes resulting from growth on gradients of guidance molecules. Here, we present the use of laser-assisted protein adsorption by photobleaching (LAPAP) to allow the fabrication of large-scale substrate-bound laminin-1 gradients to study neurite extension. We produced thousands of gradients of different slopes and analyzed the variations in neurite attraction of neuron-like cells (RGC-5). An image analysis algorithm processed bright field microscopy images, detecting each cell and quantifying the soma centroid and the initiation, terminal and turning angles of the longest neurite.

Getting the whole picture: combining throughput with content in microscopy

The increasing availability and performance of automated scientific equipment in the past decades have brought about a revolution in the biological sciences. The ease with which data can now be generated has led to a new culture of high-throughput science, in which new types of biological questions can be asked and tackled in a systematic and unbiased manner. High-throughput microscopy, also often referred to as high-content screening (HCS), allows acquisition of systematic data at the single-cell level. Moreover, it allows the visualization of an enormous array of cellular features and provides tools to quantify a large number of parameters for each cell. These features make HCS a powerful method to create data that is rich and biologically meaningful without compromising systematic capabilities. In this Commentary, we will discuss recent work, which has used HCS, to demonstrate the diversity of applications and technological solutions that are evolving in this field. Such advances are placing HCS methodologies at the frontier of high-throughput science and enable scientists to combine throughput with content to address a variety of cell biological questions.

High content screening in neurodegenerative diseases

The functional annotation of genomes, construction of molecular networks and novel drug target identification, are important challenges that need to be addressed as a matter of great urgency^1-4. Multiple complementary 'omics' approaches have provided clues as to the genetic risk factors and pathogenic mechanisms underlying numerous neurodegenerative diseases, but most findings still require functional validation⁵. For example, a recent genome wide association study for Parkinson's Disease (PD), identified many new loci as risk factors for the disease, but the underlying causative variant(s) or pathogenic mechanism is not known^{6, 7}. As each associated region can contain several genes, the functional evaluation of each of the genes on phenotypes associated with the disease, using traditional cell biology techniques would take too long.

There is also a need to understand the molecular networks that link genetic mutations to the phenotypes they cause. It is expected that disease phenotypes are the result of multiple interactions that have been disrupted. Reconstruction of these networks using traditional molecular methods would be time consuming. Moreover, network predictions from independent studies of individual components, the reductionism approach, will probably underestimate the network complexity⁸. This underestimation could, in part, explain the low success rate of drug approval due to undesirable or toxic side effects. Gaining a network perspective of disease related pathways using HT/HC cellular screening approaches, and identifying key nodes within these pathways, could lead to the identification of targets that are more suited for therapeutic intervention.

High-throughput screening (HTS) is an ideal methodology to address these issues^9-12. but traditional methods were one dimensional whole-well cell assays, that used simplistic readouts for complex biological processes. They were unable to simultaneously quantify the many phenotypes observed in neurodegenerative diseases such as axonal transport deficits or alterations in morphology properties^{13, 14}. This approach could not be used to investigate the dynamic nature of cellular processes or pathogenic events that occur in a subset of cells. To quantify such features one has to move to multi-dimensional phenotypes termed high-content screening (HCS)^{4, 15-17}. HCS is the cell-based quantification of several processes simultaneously, which provides a more detailed representation of the cellular response to various perturbations compared to HTS.

HCS has many advantages over HTS^{18, 19}, but conducting a high-throughput (HT)-high-content (HC) screen in neuronal models is problematic due to high cost, environmental variation and human error. In order to detect cellular responses on a 'phenomics' scale using HC imaging one has to reduce variation and error, while increasing sensitivity and reproducibility.

Herein we describe a method to accurately and reliably conduct shRNA screens using automated cell culturing²⁰ and HC imaging in neuronal cellular models. We describe how we have used this methodology to identify modulators for one particular protein, DJ1, which when mutated causes autosomal recessive parkinsonism²¹.

Combining the versatility of HC imaging with HT methods, it is possible to accurately quantify a plethora of phenotypes. This could subsequently be utilized to advance our understanding of the genome, the pathways involved in disease pathogenesis as well as identify potential therapeutic targets.

Neurite outgrowth assessment using high content analysis methodology

High content analysis of neurite outgrowth enables the rapid and comprehensive phenotypic assessment of individual neurons in a multiwell format amenable to high throughput assays. The resulting data are considered "high content" because multiple measurements of neuronal outgrowth and morphometric data are calculated from hundreds of individual cells within each image. This approach has been widely adopted by the pharmaceutical industry to accelerate neurological drug discovery and in vitro safety assessment. High content technology utilizes automated fluorescent and/or brightfield microscopy for image acquisition. The acquired images are then quantified using mathematical algorithms to measure pertinent neurobiological morphometric information, including neurite length, count, and extent of branching for each cell within the images. Furthermore, evaluation of the individual cell-level measurements enables the detection of subpopulations of cellular responders not apparent when examining well-level averages. Using this technology, neurite outgrowth can be quantified in each well, derived from hundreds of cell measurements in a 96-well microplate in approximately 30 min.

Isoflurane decreases self-renewal capacity of rat cultured neural stem cells

BACKGROUND

In models, isoflurane produces neural and behavioral deficits in vitro and in vivo. This study tested the hypothesis that neural stem cells are adversely affected by isoflurane such that it inhibits proliferation and kills these cells.

METHODS

Sprague-Dawley rat embryonic neural stem cells were plated onto 96-well plates and treated with isoflurane, 0.7, 1.4, or 2.8%, in 21% oxygen for 6 h and fixed either at the end of treatment or 6 or 24 h later. Control plates received 21% oxygen under identical conditions. Cell proliferation was assessed immunocytochemically using 5-ethynyl-2'-deoxyuridine incorporation and death by propidium iodide staining, lactate dehydrogenase release, and nuclear expression of cleaved caspase 3. Data were analyzed at each concentration using an ANOVA; P < 0.05 was considered significant.

RESULTS

Isoflurane did not kill neural stem cells by any measure at any time. Isoflurane, 1.4 and 2.8%, reduced cell proliferation based upon 5-ethynyl-2'-deoxyuridine incorporation, whereas isoflurane, 0.7%, had no effect. At 24 h after treatment, the net effect was a 20-30% decrease in the number of cells in culture.

CONCLUSIONS

Isoflurane does not kill neural stem cells in vitro. At concentrations at and above the minimum alveolar concentrations required for general anesthesia (1.4 and 2.8%), isoflurane inhibits proliferation of these cells but has no such effect at a subminimum alveolar concentration (0.7%). These data imply that dosages of isoflurane at and above minimum alveolar concentrations may reduce the pool of neural stem cells in vivo but that lower dosages may be devoid of such effects.

High throughput object-based image analysis of β-amyloid plaques in human and transgenic mouse brain

Advances in imaging technology have enabled automated approaches for quantitative image analysis. In this study, a high content object based image analysis method was developed for quantification of β-amyloid (Aβ) plaques in postmortem brains of Alzheimer's disease (AD) subjects and in transgenic mice over overexpressing Aβ. Digital images acquired from immunohistochemically stained sections of the superior frontal gyrus were analyzed for Aβ plaque burden using a Definiens object-based segmentation approach. Blinded evaluation of Aβ stained sections from AD and aged matched human subjects accurately identified AD cases with one exception. Brains from transgenic mice overexpressing Aβ (PS1APP mice) were also evaluated by our Definiens object based image analysis approach. We observed an age-dependent increase in the amount of Aβ plaque load that we quantified in both the hippocampus and cortex. From the contralateral hemisphere, we measured the amount of Aβ in brain homogenates biochemically and observed a significant correlation between our biochemical measurements and those that we measured by our object based Definiens system in the hippocampus. Assessment of Aβ plaque load in PS1APP mice using a manual segmentation technique (Image-Pro Plus) confirmed the results of our object-based image analysis approach. Image acquisition and analysis of 32 stained human slides and 100 mouse slides were executed in 8 h and 22 h, respectively supporting the relatively high throughput features of the Definiens platform. The data show that digital imaging combined with object based image analysis is a reliable and efficient approach to quantifying Aβ plaques in human and mouse brain.

High-content screening of peptide-based non-viral gene delivery systems

High-content screening (HCS) uses high-capacity automated fluorescence imaging for the quantitative analysis of single cells and cell populations. Here, we developed an HCS assay for rapid screening of non-viral gene delivery systems as exemplified by the screening of a small library of peptide-based transfectants. These peptides were simultaneously screened for transfection efficiency, cytotoxicity, induction of cell permeability and the capacity to transfect non-dividing cells. We demonstrated that HCS is a valuable extension to the already existing screening methods for the in vitro evaluation of non-viral gene delivery systems with the added value that multiple parameters can be screened in parallel thereby obtaining more information from a single screening event, which will accelerate the development of novel gene delivery systems.

Towards a more robust approach to selecting and prosecuting promising targets and compounds

There are many factors that influence predictivity in drug discovery and impact on productivity within the pharmaceutical industry. This article will concentrate on just two aspects; first, the role of investigating target modulation within a (human) disease setting, from target selection through screening to animal models, and second, potential developments in the analysis and probing of the chemical space appropriate for drug discovery and, in particular, steps to improve predictivity thus moving to a more forward-looking process. The activities associated with target selection should develop significantly over the next 5-10 years leading to a more robust association of target modulation with disease modification. In addition, better understanding of the opportunities for target modulators should drive and improve the selection of ligands suitable for therapeutic applications. Within these areas it will be important to move away from a retrospective consideration of druggable targets towards a forward-looking approach based on holistic (disease context) profiling of both (progressable) targets and subsequently their ligands. Improvements in the predictive analysis and probing of the chemical space will be needed to confront both safety and efficacy end points that currently remain major reasons for failure in the clinic. It is hoped that improvements in data visualization together with chemocentric mining of the literature will facilitate better interrogation of development and clinical data, potentially modifying research project plans to better address these key issues.

Quantification of hormone sensitive lipase phosphorylation and colocalization with lipid droplets in murine 3T3L1 and human subcutaneous adipocytes via automated digital microscopy and high-content analysis

Lipolysis in adipocytes is associated with phosphorylation of hormone sensitive lipase (HSL) and translocation of HSL to lipid droplets. In this study, adipocytes were cultured in a high-throughput format (96-well dishes), exposed to lipolytic agents, and then fixed and labeled for nuclei, lipid droplets, and HSL (or HSL phosphorylated on serine 660 [pHSLser660]). The cells were imaged via automated digital fluorescence microscopy, and high-content analysis (HCA) methods were used to quantify HSL phosphorylation and the degree to which HSL (or pHSLser660) colocalizes with the lipid droplets. HSL:lipid droplet colocalization was quantified through use of Pearson's correlation, Mander's M1 Colocalization, and the Tanimoto coefficient. For murine 3T3L1 adipocytes, isoproterenol, Lys-γ3-melanocyte stimulating hormone, and forskolin elicited the appearance and colocalization of pHSLser660, whereas atrial natriuretic peptide (ANP) did not. For human subcutaneous adipocytes, isoproterenol, forskolin, and ANP activated HSL phosphorylation/colocalization, but Lys-γ3-melanocyte stimulating hormone had little or no effect. Since ANP activates guanosine 3',5'-cyclic monophosphate (cGMP)-dependent protein kinase, HSL serine 660 is likely a substrate for cGMP-dependent protein kinase in human adipocytes. For both adipocyte model systems, adipocytes with the greatest lipid content displayed the greatest lipolytic responses. The results for pHSLser660 were consistent with release of glycerol by the cells, a well-established assay of lipolysis, and the HCA methods yielded Z' values >0.50. The results illustrate several key differences between human and murine adipocytes and demonstrate advantages of utilizing HCA techniques to study lipolysis in cultured adipocytes.

Automated Sholl analysis of digitized neuronal morphology at multiple scales: Whole cell Sholl analysis versus Sholl analysis of arbor subregions

The morphology of dendrites and the axon determines how a neuron processes and transmits information. Neurite morphology is frequently analyzed by Sholl analysis or by counting the total number of neurites and branch tips. However, the time and resources required to perform such analysis by hand is prohibitive for the processing of large data sets and introduces problems with data auditing and reproducibility. Furthermore, analyses performed by hand or using course-grained morphometric data extraction tools can obscure subtle differences in data sets because they do not store the data in a form that facilitates the application of multiple analytical tools. To address these shortcomings, we have developed a program (titled "Bonfire") to facilitate digitization of neurite morphology and subsequent Sholl analysis. Our program builds upon other available open-source morphological analysis tools by performing Sholl analysis on subregions of the neuritic arbor, enabling the detection of local level changes in dendrite and axon branching behavior. To validate this new tool, we applied Bonfire analysis to images of hippocampal neurons treated with 25 ng/ml brain-derived neurotrophic factor (BDNF) and untreated control neurons. Consistent with prior findings, conventional Sholl analysis revealed that global exposure to BDNF increases the number of neuritic intersections proximal to the soma. Bonfire analysis additionally uncovers that BDNF treatment affects both root processes and terminal processes with no effect on intermediate neurites. Taken together, our data suggest that global exposure of hippocampal neurons to BDNF results in a reorganization of neuritic segments within their arbors, but not necessarily a change in their number or length. These findings were only made possible by the neurite-specific Sholl data returned by Bonfire analysis.

A rapid, inexpensive high throughput screen method for neurite outgrowth

Neurite outgrowth assays are the most common phenotypic screen to assess chemical effects on neuronal cells. Current automated assays involve expensive equipment, lengthy sample preparation and handling, costly reagents and slow rates of data acquisition and analysis. We have developed a high throughput screen (HTS) for neurite outgrowth using a robust neuronal cell model coupled to fast and inexpensive visualization methods, reduced data volume and rapid data analysis. Neuroscreen-1 (NS-1) cell, a subclone of PC12, possessing rapid growth and enhanced sensitivity to NGF was used as a model neuron. This method reduces preparation time by using cells expressing GFP or native cells stained with HCS CellMask(™) Red in a multiplexed 30 min fixation and staining step. A 2x2 camera binning process reduced both image data files and analysis times by 75% and 60% respectively, compared to current protocols. In addition, eliminating autofocus steps during montage generation reduced data collection time. Pharmacological profiles for stimulation and inhibition of neurite outgrowth by NGF and SU6656 were comparable to current standard method utilizing immunofluorescence detection of tubulin. Potentiation of NGF-induced neurite outgrowth by members of a 1,120-member Prestwick compound library as assayed using this method identified six molecules, including etoposide, isoflupredone acetate, fludrocortisone acetate, thioguanosine, oxyphenbutazone and gibberellic acid, that more than doubled the neurite mass primed by 2 ng/ml NGF. This simple procedure represents an important routine approach in high throughput screening of large chemical libraries using the neurite outgrowth phenotype as a measure of the effects of chemical molecules on neuronal cells.

Modeling complex neuropsychiatric disease with induced pluripotent stem cells

The study of neuropsychiatric diseases and the development of effective treatments have been limited by a lack of appropriate models. Induced pluripotent stem cells (iPSCs) represent a potentially limitless supply of patient-specific cells for the study of neuropsychiatric disorders. In this review, we will discuss the potential and limitations of iPSCs for the development of cell-based models of neuropsychiatric diseases and the identification of novel therapeutics.

From single genes to gene networks: high-throughput-high-content screening for neurological disease

Neuronal development, function, and the subsequent degeneration of the brain are still an enigma in both the normal and pathologic states, and there is an urgent need to find better targets for developing therapeutic intervention. Current techniques to deconstruct the architecture of brain and disease-related pathways are best suited for following up on single genes but would take an impractical amount of time for the leads from the current wave of genetic and genomic data. New technical developments have made combined high-throughput-high-content (HT-HC) cellular screens possible, which have the potential to contextualize the information, gathered from a combination of genetic and genomic approaches, into networks and functional biology and can be utilized for the identification of therapeutic targets. Herein we discuss the potential impact of HT-HC cellular screens on medical neuroscience.

Automatic robust neurite detection and morphological analysis of neuronal cell cultures in high-content screening

Cell-based high content screening (HCS) is becoming an important and increasingly favored approach in therapeutic drug discovery and functional genomics. In HCS, changes in cellular morphology and biomarker distributions provide an information-rich profile of cellular responses to experimental treatments such as small molecules or gene knockdown probes. One obstacle that currently exists with such cell-based assays is the availability of image processing algorithms that are capable of reliably and automatically analyzing large HCS image sets. HCS images of primary neuronal cell cultures are particularly challenging to analyze due to complex cellular morphology. Here we present a robust method for quantifying and statistically analyzing the morphology of neuronal cells in HCS images. The major advantages of our method over existing software lie in its capability to correct non-uniform illumination using the contrast-limited adaptive histogram equalization method; segment neuromeres using Gabor-wavelet texture analysis; and detect faint neurites by a novel phase-based neurite extraction algorithm that is invariant to changes in illumination and contrast and can accurately localize neurites. Our method was successfully applied to analyze a large HCS image set generated in a morphology screen for polyglutamine-mediated neuronal toxicity using primary neuronal cell cultures derived from embryos of a Drosophila Huntington's Disease (HD) model.

A Personal Perspective on High-Content Screening (HCS)

High-content screening (HCS) was introduced in 1997 based on light microscope imaging technologies to address the need for an automated platform that could analyze large numbers of individual cells with subcellular resolution using standard microplates. Molecular specificity based on fluorescence was a central element of the platform taking advantage of the growing list of reagent classes and the ability to multiplex. In addition, image analysis coupled to data management, data mining, and data visualization created a tool that focused on biological information and knowledge to begin exploring the functions of genes identified in the genomics revolution. This overview looks at the development of HCS, the evolution of the technologies, and the market up to the present day. In addition, the options for adopting uniform definitions is suggested along with a perspective on what advances are needed to continue building the value of HCS in biomedical research, drug discovery, and development and diagnostics.