Identification of small molecule inhibitors of neurite loss induced by Aß peptide using high content screening.

Multiple lines of evidence indicate a strong relationship between Αß peptide-induced neurite degeneration and the progressive loss of cognitive functions in Alzheimer disease (AD) patients and in AD animal models. This prompted us to develop a high content screening assay (HCS) and Neurite Image Quantitator (NeuriteIQ) software to quantify the loss of neuronal projections induced by Aß peptide neurons and enable us to identify new classes of neurite-protective small molecules, which may represent new leads for AD drug discovery. We identified thirty-six inhibitors of Aß-induced neurite loss in the 1,040-compound National Institute of Neurological Disorders and Stroke (NINDS) custom collection of known bioactives and FDA approved drugs. Activity clustering showed that non-steroidal anti-inflammatory drugs (NSAIDs) were significantly enriched among the hits. Notably, NSAIDs have previously attracted significant attention as potential drugs for AD; however their mechanism of action remains controversial. Our data revealed that cyclooxygenase-2 (COX-2) expression was increased following Aß treatment. Furthermore, multiple distinct classes of COX inhibitors efficiently blocked neurite loss in primary neurons, suggesting that increased COX activity contributes to Aß peptide-induced neurite loss. Finally, we discovered that the detrimental effect of COX activity on neurite integrity may be mediated through the inhibition of peroxisome proliferator-activated receptor γ (PPARγ) activity. Overall, our work establishes the feasibility of identifying small molecule inhibitors of Aß-induced neurite loss using the NeuriteIQ pipeline and provides novel insights into the mechanisms of neuroprotection by NSAIDs.

Cell death assays for drug discovery.

Cell death has an important role in many human diseases, and strategies aimed at modulating the associated pathways have been successfully applied to treat various disorders. Indeed, several clinically promising cytotoxic and cytoprotective agents with potential applications in cancer, ischaemic and neurodegenerative diseases have recently been identified by high-throughput screening (HTS), based on appropriate cell death assays. Given that different cell death modalities may be dysregulated in different diseases, it is becoming increasingly clear that such assays need to not only quantify the extent of cell death, but they must also be able to distinguish between the various pathways. Here, we systematically describe approaches to accurately quantify distinct cell death pathways, discuss their advantages and pitfalls, and focus on those techniques that are amenable to HTS.

Automated neurite extraction using dynamic programming for high-throughput screening of neuron-based assays.

High-throughput screening (HTS) of cell-based assays has recently emerged as an important tool of drug discovery. The analysis and modeling of HTS microscopy neuron images, however, is particularly challenging. In this paper we present a novel algorithm for extraction and quantification of neurite segments from HTS neuron images. The algorithm is designed to be able to detect and link neurites even with complex neuronal structures and of poor imaging quality. Our proposed algorithm automatically detects initial seed points on a set of grid lines and estimates the ending points of the neurite by iteratively tracing the centerline points along the line path representing the neurite segment. The live-wire method is then applied to link the seed points and the corresponding ending points using dynamic programming techniques, thus enabling the extraction of the centerlines of the neurite segments accurately and robustly against noise, discontinuity, and other image artifacts. A fast implementation of our algorithm using dynamic programming is also provided in the paper. Any thin neurite and its segments with low intensity contrast can be well preserved by detecting the starting and ending points of the neurite. All these properties make the proposed algorithm attractive for high-throughput screening of neuron-based assays.