Automated detection of apoptotic versus nonapoptotic cell death using label‐free computational microscopy. Issue 4 (9th January 2022)

• Record Type: Journal Article
• Authors: Kabir, Md Alamgir; Kharel, Ashish; Malla, Saloni; Kreis, Zachary Joseph; Nath, Peuli; Wolfe, Jared Neil; Hassan, Marwa; Kaur, Devinder; Sari‐Sarraf, Hamed; Tiwari, Amit K.; Ray, Aniruddha
• Is Part Of: Journal of biophotonics. Volume 15:Issue 4(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-01-09
• Subjects: anticancer drug development -- cell death -- drug resistance -- holographic microscopy -- lensless microscopy -- widefield microscopy; Photonics -- Periodicals; Optical materials -- Periodicals; Optics -- Periodicals; Medical instruments and apparatus -- Periodicals; 621.3605
• DOI: 10.1002/jbio.202100310
• Languages: English
• ISSNs: 1864-063X

Abstract

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. Abstract : Here, we present a high‐throughput label‐free method for detection of cell death mechanism induced by chemotherapeutic drugs. This method combines lensless digital holographic microscopy with deep learning to enable real‐time analysis of more than a thousand cells at a time, which has the potential to significantly accelerate the drug‐screening process.