Researchers at Harvard Medical School and the Koch Institute for Integrative Cancer Research at Massachusetts Institute of Technology have developed a system that allows them to study individual human neurons and other nervous system cells. Researchers have identified the subpopulations of cells responsible for the secretion of Alzheimer’s disease-relevant factors such as amyloid β (Aβ) protein, discoveries that can allow a deeper understanding of the disease and the monitoring of single-cell responses to therapeutic drugs.
The research paper, “Single-Cell Detection of Secreted Aβ and sAPPα from Human IPSC-Derived Neurons and Astrocytes,” was published in the Journal of Neuroscience.
J. Christopher Love, from the Koch Institute for Integrative Cancer Research at MIT, developed a system that allows researchers to look at individual immune system cells, such as B-cells and T-cells. In collaboration with Tracy Young-Pearse’s team from Harvard Medical School, the team was able to apply this system to neuroscience and to the study neurological diseases. The researchers established, for the first time, a technology that detects and measures amyloid β (Aβ) and soluble amyloid precursor protein-alpha (sAPPα), factors that are central to Alzheimer’s pathogenesis.
According to the authors, the discoveries made in this study would not have been possible without a single-cell analytical platform, a research system at a massive scale that allows, in a one slide, the analysis of 86,000 single cells. Several genetic and immunostaining analyses led to the identification of previously unknown biological behaviours of APP. Moreover, it was observed that multiple cells secrete high levels of Aβ and sAPPα, namely astrocytes, which might have an important role in Aβ accumulation and plaque formation in the brain.
Researchers believe this technology can be readily applied for the detection of biomarkers, further enlightening the knowledge of central nervous system dysfunction and paving the way for novel therapeutic avenues. “We didn’t have the ability to do this until recently,” Young-Pearse said in a news release. “The amount of heterogeneity between two cells that you think are the same can actually be huge. There are incredible differences between cell types. And we finally have the ability to look at those differences on the single cell level.”
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