LAPSE:2018.0329
Published Article
LAPSE:2018.0329
Measuring Cellular Biomass Composition for Computational Biology Applications
Ashley E. Beck, Kristopher A. Hunt, Ross P. Carlson
July 31, 2018
Computational representations of metabolism are increasingly common in medical, environmental, and bioprocess applications. Cellular growth is often an important output of computational biology analyses, and therefore, accurate measurement of biomass constituents is critical for relevant model predictions. There is a distinct lack of detailed macromolecular measurement protocols, including comparisons to alternative assays and methodologies, as well as tools to convert the experimental data into biochemical reactions for computational biology applications. Herein is compiled a concise literature review regarding methods for five major cellular macromolecules (carbohydrate, DNA, lipid, protein, and RNA) with a step-by-step protocol for a select method provided for each macromolecule. Additionally, each method was tested on three different bacterial species, and recommendations for troubleshooting and testing new species are given. The macromolecular composition measurements were used to construct biomass synthesis reactions with appropriate quality control metrics such as elemental balancing for common computational biology methods, including flux balance analysis and elementary flux mode analysis. Finally, it was demonstrated that biomass composition can substantially affect fundamental model predictions. The effects of biomass composition on in silico predictions were quantified here for biomass yield on electron donor, biomass yield on electron acceptor, biomass yield on nitrogen, and biomass degree of reduction, as well as the calculation of growth associated maintenance energy; these parameters varied up to 7%, 70%, 35%, 12%, and 40%, respectively, between the reference biomass composition and ten test biomass compositions. The current work furthers the computational biology community by reviewing literature regarding a variety of common analytical measurements, developing detailed procedures, testing the methods in the laboratory, and applying the results to metabolic models, all in one publicly available resource.
Keywords
biomass reaction, computational biology, macromolecular composition, metabolic model, methods
Subject
Suggested Citation
Beck AE, Hunt KA, Carlson RP. Measuring Cellular Biomass Composition for Computational Biology Applications. (2018). LAPSE:2018.0329
Author Affiliations
Beck AE: Microbiology and Immunology, Center for Biofilm Engineering, Montana State University, Bozeman, MT 59717, USA
Hunt KA: Civil and Environmental Engineering, University of Washington, Seattle, WA 98195, USA [ORCID]
Carlson RP: Chemical and Biological Engineering, Center for Biofilm Engineering, Montana State University, Bozeman, MT 59717, USA
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Journal Name
Processes
Volume
6
Issue
5
Article Number
E38
Year
2018
Publication Date
2018-04-24
Published Version
ISSN
2227-9717
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Original Submission
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PII: pr6050038, Publication Type: Journal Article
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LAPSE:2018.0329
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doi:10.3390/pr6050038
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Jul 31, 2018
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CC BY 4.0
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