Types of cell death and apoptotic stages in Chinese Hamster Ovary cells distinguished by Raman spectroscopy

Abstract

Cell death is the ultimate cause of productivity loss in bioreactors that are used to produce therapeutic proteins. We investigated the ability of Raman spectroscopy to detect the onset and types of cell death for Chinese Hamster Ovary (CHO) cells-the most widely used cell type for therapeutic protein production. Raman spectroscopy was used to compare apoptotic, necrotic, autophagic, and control CHO cells. Several specific nucleic acid-, protein-, and lipid-associated marker bands within the 650-850 cm spectral region were identified that distinguished among cells undergoing different modes of cell death; supporting evidence was provided by principal component analysis (PCA) of the full spectral data. In addition to comparing the different modes of cell death, normal cells were compared to cells sorted at several stages of apoptosis, in order to explore the potential for early detection of apoptosis. Different stages of apoptosis could be distinguished via Raman spectroscopy, with multiple changes observed in nucleic acid peaks at early stages whereas an increase in lipid signals was a feature of late apoptosis/secondary necrosis.

Raman Spectroscopy Follows Time-Dependent Changes in T Lymphocytes Isolated from Spleen of Endotoxemic Mice

“…This was also noted in the color of spleen after isolation, spleens of LPS-treated mice appearing pale-red color, whereas spleen from control mice were deep red (data not shown). However, the general anemic conditions of the animals were recorded from blood hemogram and have been previously reported (see figure 1D of absence of prominent DNA phosphate backbone vibration contributions in the treated mice, as observed from the LD loading, points in the direction of internucleosomal DNA cleavage of the apoptotic cells present in the tissue (51,54,63). The bright-field spleen tissue images of the LPS-treated mice in comparison with the control show scarring and tissue injury (Fig.…”

“…This is reflected in the Raman spectra 30 d post-LPS insult that feature Raman peaks arising from DNA. These changes observed in T cells have been attributed to genomic rearrangements, as such transformation affects the compactness of chromatin as reported by Chan et al (33) and hence the variation in the nucleus Raman peak intensities (54). Further, to sustain the large changes in the nucleus, large numbers of proteins are required in the activated T cells compared with the naive cells.…”

Raman spectra‐based deep learning: A tool to identify microbial contamination

“…The overnight grown cultures were fixed with 2.5% of glutaraldehyde and washed with water to remove the debris and diluted to a concentration of 10 5 cells/ml for Raman dataset development. The CHO cells were cultured up to 80% confluent in T75 cell culture flask, and the cells were trypsinized and processed for Raman spectroscopy as mentioned by Rangan et al (2018). 10 5 cells/ml of CHO cells were measured using the Invitrogen Countess™ Automated Cell Counter.…”

Enabling PAT in insect cell bioprocesses: In situ monitoring of recombinant adeno‐associated virus production by fluorescence spectroscopy

“…Several spectroscopic techniques have been used for cell culture process and virus production monitoring, with Raman (Rangan et al, 2018;Santos, Kessler, Salou, Menezes, & Peinado, 2018;Webster, Hadley, Hilliard, Jaques, & Mason, 2018), near-infrared (Mercier et al, 2015;Rowland-Jones, van den Berg, Racher, Martin, & Jaques, 2017), dielectric (Kroll, Stelzer, & Herwig, 2017;Mercier et al, 2015;Nikolay, Léon, Schwamborn, Genzel, & Reichl, 2018;Petiot, Ansorge, Rosa-Calatrava, & Kamen, 2016) and fluorescence spectroscopy (Karakach et al, 2018;Schwab & Hesse, 2017) being the most widely used. All possess characteristics desirable for PAT: spectroscopic techniques are noninvasive, nondestructive, and able to provide rapid information from several components simultaneously (Ohadi, Aghamohseni, Legge, & Budman, 2014;Ohadi, Legge, & Budman, 2015;Rowland-Jones et al, 2017;Teixeira et al, 2011Teixeira et al, , 2009, including product quality attributes (Chopda, Pathak, Batra, Gomes, & Rathore, 2017;Li et al, 2019).…”