|
1
|
Dodia H, Sunder AV, Borkar Y, Wangikar PP. Precision fermentation with mass spectrometry-based spent media analysis. Biotechnol Bioeng 2023; 120:2809-2826. [PMID: 37272489 DOI: 10.1002/bit.28450] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 05/13/2023] [Accepted: 05/15/2023] [Indexed: 06/06/2023]
Abstract
Optimization and monitoring of bioprocesses requires the measurement of several process parameters and quality attributes. Mass spectrometry (MS)-based techniques such as those coupled to gas chromatography (GCMS) and liquid Chromatography (LCMS) enable the simultaneous measurement of hundreds of metabolites with high sensitivity. When applied to spent media, such metabolome analysis can help determine the sequence of substrate uptake and metabolite secretion, consequently facilitating better design of initial media and feeding strategy. Furthermore, the analysis of metabolite diversity and abundance from spent media will aid the determination of metabolic phases of the culture and the identification of metabolites as surrogate markers for product titer and quality. This review covers the recent advances in metabolomics analysis applied to the development and monitoring of bioprocesses. In this regard, we recommend a stepwise workflow and guidelines that a bioprocesses engineer can adopt to develop and optimize a fermentation process using spent media analysis. Finally, we show examples of how the use of MS can revolutionize the design and monitoring of bioprocesses.
Collapse
Affiliation(s)
- Hardik Dodia
- Department of Chemical Engineering, Indian Institute of Technology Bombay, Powai, Mumbai, India
| | | | - Yogen Borkar
- Clarity Bio Systems India Pvt. Ltd., Pune, India
| | - Pramod P Wangikar
- Department of Chemical Engineering, Indian Institute of Technology Bombay, Powai, Mumbai, India
- Clarity Bio Systems India Pvt. Ltd., Pune, India
| |
Collapse
|
|
2
|
Telu KH, Marupaka R, Andriamaharavo NR, Simón-Manso Y, Liang Y, Mirokhin YA, Bukhari TH, Preston RJ, Kashi L, Kelman Z, Stein SE. Creation and filtering of a recurrent spectral library of CHO cell metabolites and media components. Biotechnol Bioeng 2021; 118:1491-1510. [PMID: 33404064 PMCID: PMC8048470 DOI: 10.1002/bit.27661] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2020] [Revised: 12/02/2020] [Accepted: 12/13/2020] [Indexed: 02/02/2023]
Abstract
This paper reports the first implementation of a new type of mass spectral library for the analysis of Chinese hamster ovary (CHO) cell metabolites that allows users to quickly identify most compounds in any complex metabolite sample. We also describe an annotation methodology developed to filter out artifacts and low‐quality spectra from recurrent unidentified spectra of metabolites. CHO cells are commonly used to produce biological therapeutics. Metabolic profiles of CHO cells and media can be used to monitor process variability and look for markers that discriminate between batches of product. We have created a comprehensive library of both identified and unidentified metabolites derived from CHO cells that can be used in conjunction with tandem mass spectrometry to identify metabolites. In addition, we present a workflow that can be used for assigning confidence to a NIST MS/MS Library search match based on prior probability of general utility. The goal of our work is to annotate and identify (when possible), all liquid chromatography‐mass spectrometry generated metabolite ions as well as create automatable library building and identification pipelines for use by others in the field.
Collapse
Affiliation(s)
- Kelly H Telu
- Mass Spectrometry Data Center, Biomolecular Measurement Division, National Institute of Standards and Technology, Gaithersburg, Maryland, USA
| | - Ramesh Marupaka
- Mass Spectrometry Data Center, Biomolecular Measurement Division, National Institute of Standards and Technology, Gaithersburg, Maryland, USA
| | - Nirina R Andriamaharavo
- Mass Spectrometry Data Center, Biomolecular Measurement Division, National Institute of Standards and Technology, Gaithersburg, Maryland, USA
| | - Yamil Simón-Manso
- Mass Spectrometry Data Center, Biomolecular Measurement Division, National Institute of Standards and Technology, Gaithersburg, Maryland, USA
| | - Yuxue Liang
- Mass Spectrometry Data Center, Biomolecular Measurement Division, National Institute of Standards and Technology, Gaithersburg, Maryland, USA
| | - Yuri A Mirokhin
- Mass Spectrometry Data Center, Biomolecular Measurement Division, National Institute of Standards and Technology, Gaithersburg, Maryland, USA
| | - Tallat H Bukhari
- Mass Spectrometry Data Center, Biomolecular Measurement Division, National Institute of Standards and Technology, Gaithersburg, Maryland, USA
| | - Renae J Preston
- Biomolecular Labeling Laboratory, Institute for Bioscience and Biotechnology Research, National Institute of Standards and Technology and the University of Maryland, Rockville, Maryland, USA
| | - Lila Kashi
- Biomolecular Labeling Laboratory, Institute for Bioscience and Biotechnology Research, National Institute of Standards and Technology and the University of Maryland, Rockville, Maryland, USA
| | - Zvi Kelman
- Biomolecular Labeling Laboratory, Institute for Bioscience and Biotechnology Research, National Institute of Standards and Technology and the University of Maryland, Rockville, Maryland, USA
| | - Stephen E Stein
- Mass Spectrometry Data Center, Biomolecular Measurement Division, National Institute of Standards and Technology, Gaithersburg, Maryland, USA
| |
Collapse
|