Literature DB >> 29030978

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

Shreyas Rangan1,2, Sepehr Kamal1,2, Stanislav O Konorov2,3, Hans Georg Schulze2,3, Michael W Blades4, Robin F B Turner2,3, James M Piret1,2,5.   

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-1 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.
© 2017 Wiley Periodicals, Inc.

Entities:  

Keywords:  Chinese hamster ovary cells; Raman spectroscopy; apoptosis; autophagy; cell death; necrosis

Mesh:

Substances:

Year:  2017        PMID: 29030978     DOI: 10.1002/bit.26476

Source DB:  PubMed          Journal:  Biotechnol Bioeng        ISSN: 0006-3592            Impact factor:   4.530


  4 in total

1.  Development of an inexpensive Raman-compatible substrate for the construction of a microarray screening platform.

Authors:  Isamar Pastrana-Otero; Sayani Majumdar; Aidan E Gilchrist; Brittney L Gorman; Brendan A C Harley; Mary L Kraft
Journal:  Analyst       Date:  2020-10-26       Impact factor: 4.616

2.  Raman spectra-based deep learning: A tool to identify microbial contamination.

Authors:  Murali K Maruthamuthu; Amir Hossein Raffiee; Denilson Mendes De Oliveira; Arezoo M Ardekani; Mohit S Verma
Journal:  Microbiologyopen       Date:  2020-10-16       Impact factor: 3.139

Review 3.  The role of Raman spectroscopy in biopharmaceuticals from development to manufacturing.

Authors:  Karen A Esmonde-White; Maryann Cuellar; Ian R Lewis
Journal:  Anal Bioanal Chem       Date:  2021-10-20       Impact factor: 4.142

Review 4.  DNA damage in preimplantation embryos and gametes: specification, clinical relevance and repair strategies.

Authors:  Richard Musson; Łukasz Gąsior; Simona Bisogno; Grażyna Ewa Ptak
Journal:  Hum Reprod Update       Date:  2022-05-02       Impact factor: 17.179

  4 in total

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