High content screening (HCS), also known as high content analysis (HCA), has been widely used in biological research especially drug discovery for the identification of desired substances. Equipped with sensitive imaging system and reliable data analysis technology, the high content screening presents great potentials in multiple applications. As a phenotypic screening in cells, multiple parameters can be read at the same time for the analysis of whole cells or cell components. HCS has also been used in all aspects of drug development including primary compound screening, as well as early evaluation of ADME (absorption, distribution, metabolism, and excretion) and toxicity properties. Compared with high-throughput screening (HTS), HCS allows monitoring of multiple nodes in the cell pathway and the results would be more predictable.
In HCS, cells are incubated with the substance first, and then the cell structures and molecular components are analyzed through automatic image analysis. The changes in cell phenotype displayed by fluorescently labeled proteins can be obtained. Furthermore, changes at the subcellular level can also be detected, including cytoplasm, nucleus, and other organelles. In addition to fluorescent labeling, novel label-free assays have been used in HCS.
High Content Screening in Neuroscience
In neuroscience, HCS has been used in two major areas: neural regeneration and neuroprotection. There are also a series of primary neurons used in HCS, such as cerebellar granule neurons (CGNs), dorsal root ganglion (DRG) neurons, hippocampal neurons, cortical neurons, spinal cord neurons, retinal ganglion cells (RGCs), and Drosophila neurons. Through quantitative analysis of complex cell phenotypes, it is helpful for the development of drugs against neurological diseases
Fig.1 Current trends in high-content analysis in biomedicine. (Liu, 2014)
Advantages of High Content Screening Service
Reduced photobleaching and phototoxicity
Multiple points can be collected simultaneously
Faster imaging process
Effectively suppressed background
3D imaging to improve the throughput and productivity
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Liu, E.; Nolan, J. Surface Enhanced Raman Scattering (SERS) Image Cytometry for High-Content Screening. Fluorescence Microscopy. Academic Press. 2014: 93-108.