» Articles » PMID: 38086908

Deep in Situ Microscopy for Real-time Analysis of Mammalian Cell Populations in Bioreactors

Overview
Journal Sci Rep
Specialty Science
Date 2023 Dec 12
PMID 38086908
Authors
Affiliations
Soon will be listed here.
Abstract

An in situ microscope based on pulsed transmitted light illumination via optical fiber was combined to artificial-intelligence to enable for the first time an online cell classification according to well-known cellular morphological features. A 848 192-image database generated during a lab-scale production process of antibodies was processed using a convolutional neural network approach chosen for its accurate real-time object detection capabilities. In order to induce different cell death routes, hybridomas were grown in normal or suboptimal conditions in a stirred tank reactor, in the presence of substrate limitation, medium addition, pH regulation problem or oxygen depletion. Using such an optical system made it possible to monitor real-time the evolution of different classes of animal cells, among which viable, necrotic and apoptotic cells. A class of viable cells displaying bulges in feast or famine conditions was also revealed. Considered as a breakthrough in the catalogue of process analytical tools, in situ microscopy powered by artificial-intelligence is also of great interest for research.

References
1.
Pietkiewicz S, Schmidt J, Lavrik I . Quantification of apoptosis and necroptosis at the single cell level by a combination of Imaging Flow Cytometry with classical Annexin V/propidium iodide staining. J Immunol Methods. 2015; 423:99-103. DOI: 10.1016/j.jim.2015.04.025. View

2.
Heins A, Weuster-Botz D . Population heterogeneity in microbial bioprocesses: origin, analysis, mechanisms, and future perspectives. Bioprocess Biosyst Eng. 2018; 41(7):889-916. DOI: 10.1007/s00449-018-1922-3. View

3.
Edinger A, Thompson C . Death by design: apoptosis, necrosis and autophagy. Curr Opin Cell Biol. 2004; 16(6):663-9. DOI: 10.1016/j.ceb.2004.09.011. View

4.
von Chamier L, Laine R, Jukkala J, Spahn C, Krentzel D, Nehme E . Democratising deep learning for microscopy with ZeroCostDL4Mic. Nat Commun. 2021; 12(1):2276. PMC: 8050272. DOI: 10.1038/s41467-021-22518-0. View

5.
Pekle E, Smith A, Rosignoli G, Sellick C, Smales C, Pearce C . Application of Imaging Flow Cytometry for the Characterization of Intracellular Attributes in Chinese Hamster Ovary Cell Lines at the Single-Cell Level. Biotechnol J. 2019; 14(7):e1800675. DOI: 10.1002/biot.201800675. View