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

Towards a Conceptual Framework to Better Understand the Advantages and Limitations of Model Organisms

Model organisms (MO) are widely used in neuroscience to study brain processes, behavior, and the biological foundation of human diseases. However, the use of MO has also been criticized for low reliability and insufficient success rate in the development of therapeutic approaches, because the success of MO use also led to overoptimistic and simplistic applications, which sometimes resulted in wrong conclusions. Here, we develop a conceptual framework of MO to support scientists in their practical work and to foster discussions about their power and limitations. For this purpose, we take advantage of concepts developed in the philosophy of science and adjust them for practical application by neuroscientists. We suggest that MO can be best understood as tools that are used to gain information about a group of species or a phenomenon in a species of interest. These learning processes are made possible by some properties of MO, which facilitate the process of acquisition of understanding or provide practical advantages, and the possibility to transfer information between species. However, residual uncertainty in the reliability of information transfer remains, and incorrect generalizations can be side-effects of epistemic benefits, which we consider as representational and epistemic risks. This suggests that to use MO most effectively, scientists should analyze the similarity relation between the involved species, weigh advantages and risks of certain epistemic benefits, and invest in carefully designed validation experiments. Altogether, our analysis illustrates how scientists can benefit from philosophical concepts for their research practice.

Genetic risk factors in Parkinson's disease

Over the last two decades, we have witnessed a revolution in the field of Parkinson's disease (PD) genetics. Great advances have been made in identifying many loci that confer a risk for PD, which has subsequently led to an improved understanding of the molecular pathways involved in disease pathogenesis. Despite this success, it is predicted that only a relatively small proportion of the phenotypic variability has been explained by genetics. Therefore, it is clear that common heritable components of disease are still to be identified. Dissecting the genetic architecture of PD constitutes a critical effort in identifying therapeutic targets and although such substantial progress has helped us to better understand disease mechanism, the route to PD disease-modifying drugs is a lengthy one. In this review, we give an overview of the known genetic risk factors in PD, focusing not on individual variants but the larger networks that have been implicated following comprehensive pathway analysis. We outline the challenges faced in the translation of risk loci to pathobiological relevance and illustrate the need for integrating big-data by noting success in recent work which adopts a broad-scale screening approach. Lastly, with PD genetics now progressing from identifying risk to predicting disease, we review how these models will likely have a significant impact in the future.

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.

How to make a midbrain dopaminergic neuron

Midbrain dopaminergic (mDA) neuron development has been an intense area of research during recent years. This is due in part to a growing interest in regenerative medicine and the hope that treatment for diseases affecting mDA neurons, such as Parkinson's disease (PD), might be facilitated by a better understanding of how these neurons are specified, differentiated and maintained in vivo. This knowledge might help to instruct efforts to generate mDA neurons in vitro, which holds promise not only for cell replacement therapy, but also for disease modeling and drug discovery. In this Primer, we will focus on recent developments in understanding the molecular mechanisms that regulate the development of mDA neurons in vivo, and how they have been used to generate human mDA neurons in vitro from pluripotent stem cells or from somatic cells via direct reprogramming. Current challenges and future avenues in the development of a regenerative medicine for PD will be identified and discussed.

NeuroArray: a universal interface for patterning and interrogating neural circuitry with single cell resolution

Recreation of neural network in vitro with designed topology is a valuable tool to decipher how neurons behave when interacting in hierarchical networks. In this study, we developed a simple and effective platform to pattern primary neurons in array formats for interrogation of neural circuitry with single cell resolution. Unlike many surface-chemistry-based patterning methods, our NeuroArray technique is specially designed to accommodate neuron's polarized morphologies to make regular arrays of cells without restricting their neurite outgrowth, and thus allows formation of freely designed, well-connected, and spontaneously active neural network. The NeuroArray device was based on a stencil design fabricated using a novel sacrificial-layer-protected PDMS molding method that enables production of through-structures in a thin layer of PDMS with feature sizes as small as 3 µm. Using the NeuroArray along with calcium imaging, we have successfully demonstrated large-scale tracking and recording of neuronal activities, and used such data to characterize the spiking dynamics and transmission within a diode-like neural network. Essentially, the NeuroArray is a universal patterning platform designed for, but not limited to neuron cells. With little adaption, it can be readily interfaced with other interrogation modalities for high-throughput drug testing, and for building neuron culture based live computational devices.

The anti-tumor histone deacetylase inhibitor SAHA and the natural flavonoid curcumin exhibit synergistic neuroprotection against amyloid-beta toxicity

With the trend of an increasing aged population worldwide, Alzheimer's disease (AD), an age-related neurodegenerative disorder, as one of the major causes of dementia in elderly people is of growing concern. Despite the many hard efforts attempted during the past several decades in trying to elucidate the pathological mechanisms underlying AD and putting forward potential therapeutic strategies, there is still a lack of effective treatments for AD. The efficacy of many potential therapeutic drugs for AD is of main concern in clinical practice. For example, large bodies of evidence show that the anti-tumor histone deacetylase (HDAC) inhibitor, suberoylanilidehydroxamic acid (SAHA), may be of benefit for the treatment of AD; however, its extensive inhibition of HDACs makes it a poor therapeutic. Moreover, the natural flavonoid, curcumin, may also have a potential therapeutic benefit against AD; however, it is plagued by low bioavailability. Therefore, the integrative effects of SAHA and curcumin were investigated as a protection against amyloid-beta neurotoxicity in vitro. We hypothesized that at low doses their synergistic effect would improve therapeutic selectivity, based on experiments that showed that at low concentrations SAHA and curcumin could provide comprehensive protection against Aβ_25–35-induced neuronal damage in PC12 cells, strongly implying potent synergism. Furthermore, network analysis suggested that the possible mechanism underlying their synergistic action might be derived from restoration of the damaged functional link between Akt and the CBP/p300 pathway, which plays a crucial role in the pathological development of AD. Thus, our findings provided a feasible avenue for the application of a synergistic drug combination, SAHA and curcumin, in the treatment of AD.

High-throughput genetic screen for synaptogenic factors: identification of LRP6 as critical for excitatory synapse development

Genetic screens in invertebrates have discovered many synaptogenic genes and pathways. However, similar genetic studies have not been possible in mammals. We have optimized an automated high-throughput platform that employs automated liquid handling and imaging of primary mammalian neurons. Using this platform, we have screened 3,200 shRNAs targeting 800 proteins. One of the hits identified was LRP6, a coreceptor for canonical Wnt ligands. LRP6 regulates excitatory synaptogenesis and is selectively localized to excitatory synapses. In vivo knockdown of LRP6 leads to a reduction in the number of functional synapses. Moreover, we show that the canonical Wnt ligand, Wnt8A, promotes synaptogenesis via LRP6. These results provide a proof of principle for using a high-content approach to screen for synaptogenic factors in the mammalian nervous system and identify and characterize a Wnt ligand receptor complex that is critical for the development of functional synapses in vivo.

A high-content screen identifies novel compounds that inhibit stress-induced TDP-43 cellular aggregation and associated cytotoxicity

TDP-43 is an RNA binding protein found to accumulate in the cytoplasm of brain and spinal cord from patients affected with amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD). Nuclear TDP-43 protein regulates transcription through several mechanisms, and under stressed conditions, it forms cytoplasmic aggregates that co-localize with stress granule (SG) proteins in cell culture. These granules are also found in the brain and spinal cord of patients affected with ALS and FTLD. The mechanism through which TDP-43 might contribute to neurodegenerative diseases is poorly understood. To investigate the pathophysiology of TDP-43 aggregation and to isolate potential therapeutic targets, we screened a chemical library of 75,000 compounds using high-content analysis with PC12 cells that inducibly express human TDP-43 tagged with green fluorescent protein (GFP). The screen identified 16 compounds that dose-dependently decreased the TDP-43 inclusions without significant cellular toxicity or changes in total TDP-43 expression levels. To validate the effect, we tested compounds by Western blot analysis and in a Caenorhabditis elegans model that replicates some of the relevant disease phenotypes. The hits from this assay will be useful for elucidating regulation of TDP-43, stress granule response, and possible ALS therapeutics.

Whole brain and brain regional coexpression network interactions associated with predisposition to alcohol consumption

To identify brain transcriptional networks that may predispose an animal to consume alcohol, we used weighted gene coexpression network analysis (WGCNA). Candidate coexpression modules are those with an eigengene expression level that correlates significantly with the level of alcohol consumption across a panel of BXD recombinant inbred mouse strains, and that share a genomic region that regulates the module transcript expression levels (mQTL) with a genomic region that regulates alcohol consumption (bQTL). To address a controversy regarding utility of gene expression profiles from whole brain, vs specific brain regions, as indicators of the relationship of gene expression to phenotype, we compared candidate coexpression modules from whole brain gene expression data (gathered with Affymetrix 430 v2 arrays in the Colorado laboratories) and from gene expression data from 6 brain regions (nucleus accumbens (NA); prefrontal cortex (PFC); ventral tegmental area (VTA); striatum (ST); hippocampus (HP); cerebellum (CB)) available from GeneNetwork. The candidate modules were used to construct candidate eigengene networks across brain regions, resulting in three "meta-modules", composed of candidate modules from two or more brain regions (NA, PFC, ST, VTA) and whole brain. To mitigate the potential influence of chromosomal location of transcripts and cis-eQTLs in linkage disequilibrium, we calculated a semi-partial correlation of the transcripts in the meta-modules with alcohol consumption conditional on the transcripts' cis-eQTLs. The function of transcripts that retained the correlation with the phenotype after correction for the strong genetic influence, implicates processes of protein metabolism in the ER and Golgi as influencing susceptibility to variation in alcohol consumption. Integration of these data with human GWAS provides further information on the function of polymorphisms associated with alcohol-related traits.

Automated methods for the analysis of skeletal muscle fiber size and metabolic type

It is of interest to quantify the size, shape, and metabolic subtype of skeletal muscle fibers in many areas of biomedical research. To do so, skeletal muscle samples are sectioned transversely to the length of the muscle and labeled for extracellular or membrane proteins to delineate the fiber boundaries and additionally for biomarkers related to function or metabolism. The samples are digitally photographed and the fibers "outlined" for quantification of fiber cross-sectional area (CSA) using pointing devices interfaced to a computer, which is tedious, prone to error, and can be nonobjective. Here, we review methods for characterizing skeletal muscle fibers and describe new automated techniques, which rapidly quantify CSA and biomarkers. We discuss the applications of these methods to the characterization of mitochondrial dysfunctions, which underlie a variety of human afflictions, and we present a novel approach, utilizing images from the online Human Protein Atlas to predict relationships between fiber-specific protein expression, function, and metabolism.

Expanding medicinal chemistry space

Clinically useful drugs target a relatively small number of proteins that lie within a clearly defined and chemically accessible space. However, many high value biological targets lie outside this chemical space, and an ability to access such 'intractable' targets not amenable to traditional small molecule intervention would expand treatment options and be a major boost for patients and the pharmaceutical industry. To date, success has been limited but new technologies and approaches are beginning to emerge that could provide novel lead generation capabilities that enable access to new drug target classes. We review these new approaches and their ability to provide the novel leads needed to tackle a new generation of biological targets.

Advances in epigenetics and epigenomics for neurodegenerative diseases

In the post-genomic era, epigenetic factors-literally those that are "over" or "above" genetic ones and responsible for controlling the expression and function of genes-have emerged as important mediators of development and aging; gene-gene and gene-environmental interactions; and the pathophysiology of complex disease states. Here, we provide a brief overview of the major epigenetic mechanisms (ie, DNA methylation, histone modifications and chromatin remodeling, and non-coding RNA regulation). We highlight the nearly ubiquitous profiles of epigenetic dysregulation that have been found in Alzheimer's and other neurodegenerative diseases. We also review innovative methods and technologies that enable the characterization of individual epigenetic modifications and more widespread epigenomic states at high resolution. We conclude that, together with complementary genetic, genomic, and related approaches, interrogating epigenetic and epigenomic profiles in neurodegenerative diseases represent important and increasingly practical strategies for advancing our understanding of and the diagnosis and treatment of these disorders.

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.

Molecular control of axon growth: insights from comparative gene profiling and high-throughput screening

Axon regeneration in the mammalian adult central nervous system (CNS) is limited by an intrinsically low capacity for axon growth in many CNS neurons. In contrast, embryonic, peripheral, and many nonmammalian neurons are capable of successful regeneration. Numerous studies have compared mammalian CNS neurons to their counterparts in regenerating systems in an effort to identify candidate genes that control regenerative ability. This review summarizes work using this comparative strategy and examines our current understanding of gene function in axon growth, highlighting the emergence of genome-wide expression profiling and high-throughput screening strategies to identify novel regulators of axon growth.

Light it up: highly efficient multigene delivery in mammalian cells

Multigene delivery and expression systems are emerging as key technologies for many applications in contemporary biology. We have developed new methods for multigene delivery and expression in eukaryotic hosts for a variety of applications, including production of protein complexes for structural biology and drug development, provision of multicomponent protein biologics, and cell-based assays. We implemented tandem recombineering to facilitate rapid generation of multicomponent gene expression constructs for efficient transformation of mammalian cells, resulting in homogenous cell populations. Analysis of multiple parameters in living cells may require co-expression of fluorescently tagged sensors simultaneously in a single cell, at defined and ideally controlled ratios. Our method enables such applications by overcoming currently limiting challenges. Here, we review recent multigene delivery and expression strategies and their exploitation in mammalian cells. We discuss applications in drug discovery assays, interaction studies, and biologics production, which may benefit in the future from our novel approach.

A novel high-throughput imaging system for automated analyses of avoidance behavior in zebrafish larvae

Early brain development can be influenced by numerous genetic and environmental factors, with long-lasting effects on brain function and behavior. The identification of these factors is facilitated by recent innovations in high-throughput screening. However, large-scale screening in whole organisms remains challenging, in particular when studying changes in brain function or behavior in vertebrate model systems. In this study, we present a novel imaging system for high-throughput analyses of behavior in zebrafish larvae. The three-camera system can image 12 multiwell plates simultaneously and is unique in its ability to provide local visual stimuli in the wells of a multiwell plate. The acquired images are converted into a series of coordinates, which characterize the location and orientation of the larvae. The developed imaging techniques were tested by measuring avoidance behaviors in seven-day-old zebrafish larvae. The system effectively quantified larval avoidance and revealed an increased edge preference in response to a blue or red 'bouncing ball' stimulus. Larvae also avoid a bouncing ball stimulus when it is counter-balanced with a stationary ball, but do not avoid blinking balls counter-balanced with a stationary ball. These results indicate that the seven-day-old larvae respond specifically to movement, rather than color, size, or local changes in light intensity. The imaging system and assays for measuring avoidance behavior may be used to screen for genetic and environmental factors that cause developmental brain disorders and for novel drugs that could prevent or treat these disorders.

Regeneration in the era of functional genomics and gene network analysis

What gives an organism the ability to regrow tissues and to recover function where another organism fails is the central problem of regenerative biology. The challenge is to describe the mechanisms of regeneration at the molecular level, delivering detailed insights into the many components that are cross-regulated. In other words, a broad, yet deep dissection of the system-wide network of molecular interactions is needed. Functional genomics has been used to elucidate gene regulatory networks (GRNs) in developing tissues, which, like regeneration, are complex systems. Therefore, we reason that the GRN approach, aided by next generation technologies, can also be applied to study the molecular mechanisms underlying the complex functions of regeneration. We ask what characteristics a model system must have to support a GRN analysis. Our discussion focuses on regeneration in the central nervous system, where loss of function has particularly devastating consequences for an organism. We examine a cohort of cells conserved across all vertebrates, the reticulospinal (RS) neurons, which lend themselves well to experimental manipulations. In the lamprey, a jawless vertebrate, there are giant RS neurons whose large size and ability to regenerate make them particularly suited for a GRN analysis. Adding to their value, a distinct subset of lamprey RS neurons reproducibly fail to regenerate, presenting an opportunity for side-by-side comparison of gene networks that promote or inhibit regeneration. Thus, determining the GRN for regeneration in RS neurons will provide a mechanistic understanding of the fundamental cues that lead to success or failure to regenerate.

The Complete Automation of Cell Culture

Genomic approaches provide enormous amounts of raw data with regard to genetic variation, the diversity of RNA species, and protein complement. High-throughput (HT) and high-content (HC) cellular screens are ideally suited to contextualize the information gathered from other “omic” approaches into networks and can be used for the identification of therapeutic targets. Current methods used for HT–HC screens are laborious, time-consuming, and prone to human error. The authors thus developed an automated high-throughput system with an integrated fluorescent imager for HC screens called the AI.CELLHOST. The implementation of user-defined culturing and assay plate setup parameters allows parallel operation of multiple screens in diverse mammalian cell types. The authors demonstrate that such a system is able to successfully maintain different cell lines in culture for extended periods of time as well as significantly increasing throughput, accuracy, and reproducibility of HT and HC screens.

Drug discovery in Parkinson's disease-Update and developments in the use of cellular models

Parkinson's disease (PD) is the second most common neurodegenerative disorder and is characterized by the degeneration of dopaminergic (DA) neurons within the substantia nigra. Dopamine replacement drugs remain the most effective PD treatment but only provide temporary symptomatic relief. New therapies are urgently needed, but the search for a disease-modifying treatment and a definitive understanding of the underlying mechanisms of PD has been limited by the lack of physiologically relevant models that recapitulate the disease phenotype. The use of immortalized cell lines as in vitro model systems for drug discovery has met with limited success, since efficacy and safety too often fail to translate successfully in human clinical trials. Drug discoverers are shifting their focus to more physiologically relevant cellular models, including primary neurons and stem cells. The recent discovery of induced pluripotent stem (iPS) cell technology presents an exciting opportunity to derive human DA neurons from patients with sporadic and familial forms of PD. We anticipate that these human DA models will recapitulate key features of the PD phenotype. In parallel, high-content screening platforms, which extract information on multiple cellular features within individual neurons, provide a network-based approach that can resolve temporal and spatial relationships underlying mechanisms of neurodegeneration and drug perturbations. These emerging technologies have the potential to establish highly predictive cellular models that could bring about a desperately needed revolution in PD drug discovery.