A method for the rapid analysis of neuronal proportions and neurite morphology in primary cultures

Growth and excitability at synapsin II deficient hippocampal neurons

Synapsins are neuronal phosphoproteins that fine-tune synaptic transmission and suppress seizure activity. Synapsin II (SynII) deletion produces epileptic seizures and overexcitability in neuronal networks. Early studies in primary neuronal cultures have shown that SynII deletion results in a delay in synapse formation. More recent studies at hippocampal slices have revealed increased spontaneous activity in SynII knockout (SynII(-)) mice. To reconcile these observations, we systematically re-examined synaptic transmission, synapse formation, and neurite growth in primary hippocampal neuronal cultures. We find that spontaneous glutamatergic synaptic activity was suppressed in SynII(-) neurons during the initial developmental epoch (7 days in vitro, DIV) but was enhanced at later times (12 and18 DIV). The density of synapses, transmission between connected pairs of neurons, and the number of docked synaptic vesicles were not affected by SynII deletion. However, we found that neurite outgrowth in SynII(-) neurons was suppressed during the initial developmental epoch (7 DIV) but enhanced at subsequent developmental stages (12 and18 DIV). This finding can account for the observed effect of SynII deletion on synaptic activity. To test whether the observed phenotype resulted directly from the deletion of SynII we expressed SynII in SynII(-) cultures using an adeno-associated virus (AAV). Expression of SynII at 2 DIV rescued the SynII deletion-dependent alterations in both synaptic activity and neuronal growth. To test whether the increased neurite outgrowth in SynII(-) observed at DIV 12 and18 represents an overcompensation for the initial developmental delay or results directly from SynII deletion we performed "late expression" experiments, transfecting SynII(-) cultures with AAV at 7 DIV. The late SynII expression suppressed neurite outgrowth at 12 and 18 DIV to the levels observed in control neurons, suggesting that these phenotypes directly depend on SynII. These results reveal a novel developmentally regulated role for SynII function in the control of neurite growth.

Automatic Dendritic Length Quantification for High Throughput Screening of Mature Neurons

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

Developmental neurotoxicity testing in vitro: models for assessing chemical effects on neurite outgrowth

In vitro models may be useful for the rapid toxicological screening of large numbers of chemicals for their potential to produce toxicity. Such screening could facilitate prioritization of resources needed for in vivo toxicity testing towards those chemicals most likely to result in adverse health effects. Cell cultures derived from nervous system tissue have proven to be powerful tools for elucidating cellular and molecular mechanisms of nervous system development and function, and have been used to understand the mechanism of action of neurotoxic chemicals. Recently, it has been suggested that in vitro models could be used to screen for chemical effects on critical cellular events of neurodevelopment, including differentiation and neurite growth. This review examines the use of neuronal cell cultures as an in vitro model of neurite outgrowth. Examples of the cell culture systems that are commonly used to examine the effects of chemicals on neurite outgrowth are provided, along with a description of the methods used to quantify this neurodevelopmental process in vitro. Issues relating to the relevance of the methods and models currently used to assess neurite outgrowth are discussed in the context of hazard identification and chemical screening. To demonstrate the utility of in vitro models of neurite outgrowth for the evaluation of large numbers of chemicals, efforts should be made to: (1) develop a set of reference chemicals that can be used as positive and negative controls for comparing neurite outgrowth between model systems, (2) focus on cell cultures of human origin, with emphasis on the emerging area of neural progenitor cells, and (3) use high-throughput methods to quantify endpoints of neurite outgrowth.

A fast and accurate procedure for deriving the Sholl profile in quantitative studies of neuronal morphology

The growth and elaboration of neural processes underpins the establishment of neural architecture during development and is a key facet of neural plasticity throughout life. Sholl analysis is a valuable and widely used method for quantifying the extent and complexity of neural processes in the vicinity of the neuronal soma, such as the dendritic arbors of individual neurons in vivo and neuritic arbors of individual neurons in vitro. It consists of tracing a series of concentric rings with regular radial increments centred in the neuronal soma and counting the number X(i) of processes intersecting each ring. This is a laborious and time-consuming procedure that consequently can only be applied to relatively small numbers of neurons. We propose a simpler and accurate method for deriving exactly the same information based only on the relative position, with respect to the cell soma, of the bifurcation (B(i)) and terminal points (T(i)) of processes. By means of the iterative equation X(i)=X(i-1)+B(i)-T(i,) it is possible to automatically reconstruct the complete pattern of intersections between neurites and the concentric rings. We compared our method with the conventional Sholl analysis and found that our simplified procedure is approximately five times faster permitting numerically larger samples to be analyzed. We further tested the sensitivity of our method of analysis by looking at the effect of preventing NF-kappaB signaling on BDNF-dependent neuritic growth in sensory neurons.

Design and validation of a tool for neurite tracing and analysis in fluorescence microscopy images

BACKGROUND

For the investigation of the molecular mechanisms involved in neurite outgrowth and differentiation, accurate and reproducible segmentation and quantification of neuronal processes are a prerequisite. To facilitate this task, we developed a semiautomatic neurite tracing technique. This article describes the design and validation of the technique.

METHODS

The technique was compared to fully manual delineation. Four observers repeatedly traced selected neurites in 20 fluorescence microscopy images of cells in culture, using both methods. Accuracy and reproducibility were determined by comparing the tracings to high-resolution reference tracings, using two error measures. Labor intensiveness was measured in numbers of mouse clicks required. The significance of the results was determined by a Student t-test and by analysis of variance.

RESULTS

Both methods slightly underestimated the true neurite length, but the differences were not unanimously significant. The average deviation from the true neurite centerline was a factor 2.6 smaller with the developed technique compared to fully manual tracing. Intraobserver variability in the respective measures was reduced by a factor 6.0 and 23.2. Interobserver variability was reduced by a factor 2.4 and 8.8, respectively, and labor intensiveness by a factor 3.3.

CONCLUSIONS

Providing similar accuracy in measuring neurite length, significantly improved accuracy in neurite centerline extraction, and significantly improved reproducibility and reduced labor intensiveness, the developed technique may replace fully manual tracing methods.

An algorithm for neurite outgrowth reconstruction

We present a numerical method which provides the ability to analyze digitized microscope images of retinal explants and quantify neurite outgrowth. Few parameters are required as input and limited user interaction is necessary to process an entire experiment of images. This eliminates fatigue related errors and user-related bias common to manual analysis. The method does not rely on stained images and handles images of variable quality. The algorithm is used to determine time and dose dependent, in vitro, neurotoxic effects of 1 GeV per nucleon iron particles in retinal explants. No neurotoxic effects are detected until 72 h after exposure; at 72 h, significant reductions of neurite outgrowth occurred at doses higher than 10 cGy.

Automated screening of neurite outgrowth

Outgrowth of neurites in culture is used for assessing neurotrophic activity. Neurite measurements have been performed very slowly using manual methods or more efficiently with interactive image analysis systems. In contrast, medium-throughput and noninteractive image analysis of neurite screens has not been well described. The authors report the performance of an automated image acquisition and analysis system (IN Cell Analyzer 1000) in the neurite assay. Neuro-2a (N2a) cells were plated in 96-well plates and were exposed to 6 conditions of retinoic acid. Immunofluorescence labeling of the cytoskeleton was used to detect neurites and cell bodies. Acquisition of the images was automatic. The image set was then analyzed by both manual tracing and automated algorithms. On 5 relevant parameters (number of neurites, neurite length, total cell area, number of cells, neurite length per cell), the authors did not observe a difference between the automated analysis and the manual analysis done by tracing. These data suggest that the automated system addresses the same biology as human scorers and with the same measurement precision for treatment effects. However, throughput of the automated system is orders of magnitude higher than with manual methods.

A rapid method for semi-quantitative analysis of neurite outgrowth from chick DRG explants using image analysis

Neurite outgrowth from dorsal root ganglion (DRG) explants is a method of evaluating neurotrophic activity of growth factors and neurotrophin mimetics. The drawbacks to this approach are the difficulties in quantifying the response. Neurite counts are time consuming and labour intensive, and the accuracy is often questionable due to branching and fasciculation of the neurites. We report here a method of semi-quantitative analysis of neurite outgrowth from chick DRG explants, using image analysis to quantify the area occupied by neurites emanating from the ganglion. This method is rapid, takes into account both the length and number of neurites, and is unaffected by neurite fasciculation or branching. Primary explants of chick DRGs were treated with the neurotrophins nerve growth factor (NGF) or neurotrophin-3 (NT-3) and with the compound K252a. K252b was tested for potentiation of the response to NT-3. The results show a dose dependent outgrowth of neurites from explants treated with NGF, NT-3 and K252a, and potentiation of the NT-3 response by K252b. These responses were quantified by neurite area quantification using image analysis. We conclude that neurite area measurement using image analysis provides a robust means of evaluating neurotrophic activity of growth factors and neurotrophin mimetics in vitro.