Automated algorithm development to assess survival of human neurons using longitudinal single-cell tracking: Application to synucleinopathy.

Autor:	Choi J; Yumanity Therapeutics, 40 Guest St, Boston, MA, 02135, United States of America., Kii H; Nikon Corporation, Tokyo, Japan., Nelson J; Yumanity Therapeutics, 40 Guest St, Boston, MA, 02135, United States of America., Yamazaki Y; Nikon Corporation, Tokyo, Japan., Yanagawa F; Nikon Instruments, New York, United States of America., Kitajima A; Nikon Corporation, Tokyo, Japan., Uozumi T; Nikon Corporation, Tokyo, Japan., Kiyota Y; Nikon Corporation, Tokyo, Japan., Doshi D; Yumanity Therapeutics, 40 Guest St, Boston, MA, 02135, United States of America., Rhodes K; Yumanity Therapeutics, 40 Guest St, Boston, MA, 02135, United States of America., Scannevin R; Yumanity Therapeutics, 40 Guest St, Boston, MA, 02135, United States of America., Sadlish H; Yumanity Therapeutics, 40 Guest St, Boston, MA, 02135, United States of America., Chung CY; Yumanity Therapeutics, 40 Guest St, Boston, MA, 02135, United States of America.
Jazyk:	angličtina
Zdroj:	SLAS technology [SLAS Technol] 2023 Apr; Vol. 28 (2), pp. 63-69. Date of Electronic Publication: 2022 Nov 29.
DOI:	10.1016/j.slast.2022.11.003
Abstrakt:	The development of phenotypic assays with appropriate analyses is an important step in the drug discovery process. Assays using induced pluripotent stem cell (iPSC)-derived human neurons are emerging as powerful tools for drug discovery in neurological disease. We have previously shown that longitudinal single cell tracking enabled the quantification of survival and death of neurons after overexpression of α-synuclein with a familial Parkinson's disease mutation (A53T). The reliance of this method on manual counting, however, rendered the process labor intensive, time consuming and error prone. To overcome these hurdles, we have developed automated detection algorithms for neurons using the BioStation CT live imaging system and CL-Quant software. In the current study, we use these algorithms to successfully measure the risk of neuronal death caused by overexpression of α-synuclein (A53T) with similar accuracy and improved consistency as compared to manual counting. This novel method also provides additional key readouts of neuronal fitness including total neurite length and the number of neurite nodes projecting from the cell body. Finally, the algorithm reveals the neuroprotective effects of brain-derived neurotrophic factor (BDNF) treatment in neurons overexpressing α-synuclein (A53T). These data show that an automated algorithm improves the consistency and considerably shortens the analysis time of assessing neuronal health, making this method advantageous for small molecule screening for inhibitors of synucleinopathy and other neurodegenerative diseases. Competing Interests: Declaration of interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)
Databáze:	MEDLINE
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