Automated detection of apoptotic versus nonapoptotic cell death using label-free computational microscopy

Md Alamgir Kabir, Ashish Kharel, Saloni Malla, Zachary Joseph Kreis, Peuli Nath, Jared Neil Wolfe, Marwa Hassan, Devinder Kaur, Hamed Sari-Sarraf, Amit K. Tiwari, Aniruddha Ray

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Identification of cell death mechanisms, particularly distinguishing between apoptotic versus nonapoptotic pathways, is of paramount importance for a wide range of applications related to cell signaling, interaction with pathogens, therapeutic processes, drug discovery, drug resistance, and even pathogenesis of diseases like cancers and neurogenerative disease among others. Here, we present a novel high-throughput method of identifying apoptotic versus necrotic versus other nonapoptotic cell death processes, based on lensless digital holography. This method relies on identification of the temporal changes in the morphological features of mammalian cells, which are unique to each cell death processes. Different cell death processes were induced by known cytotoxic agents. A deep learning-based approach was used to automatically classify the cell death mechanism (apoptotic vs necrotic vs nonapoptotic) with more than 93% accuracy. This label free approach can provide a low cost (<$250) alternative to some of the currently available high content imaging-based screening tools.

Original languageEnglish
Article numbere202100310
JournalJournal of Biophotonics
Volume15
Issue number4
DOIs
StatePublished - Apr 2022

Keywords

  • anticancer drug development
  • cell death
  • drug resistance
  • holographic microscopy
  • lensless microscopy
  • widefield microscopy

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