Model validation and selection in metabolic flux analysis and flux balance analysis

Kaste, Joshua A. M.; Shachar‐Hill, Yair

doi:10.1002/btpr.3413

Title: Model validation and selection in metabolic flux analysis and flux balance analysis

Journal Article · 24 November 2023 · Biotechnology Progress

DOI: https://doi.org/10.1002/btpr.3413 · OSTI ID:2221867

^[1]; Shachar‐Hill, Yair ^[2]

Department of Biochemistry and Molecular Biology Michigan State University East Lansing Michigan USA, Department of Plant Biology Michigan State University East Lansing Michigan USA
Department of Plant Biology Michigan State University East Lansing Michigan USA

Abstract 13C‐Metabolic Flux Analysis (13C‐MFA) and Flux Balance Analysis (FBA) are widely used to investigate the operation of biochemical networks in both biological and biotechnological research. Both methods use metabolic reaction network models of metabolism operating at steady state so that reaction rates (fluxes) and the levels of metabolic intermediates are constrained to be invariant. They provide estimated (MFA) or predicted (FBA) values of the fluxes through the network in vivo, which cannot be measured directly. These fluxes can shed light on basic biology and have been successfully used to inform metabolic engineering strategies. Several approaches have been taken to test the reliability of estimates and predictions from constraint‐based methods and to compare alternative model architectures. Despite advances in other areas of the statistical evaluation of metabolic models, such as the quantification of flux estimate uncertainty, validation and model selection methods have been underappreciated and underexplored. We review the history and state‐of‐the‐art in constraint‐based metabolic model validation and model selection. Applications and limitations of the χ ² ‐test of goodness‐of‐fit, the most widely used quantitative validation and selection approach in 13C‐MFA, are discussed, and complementary and alternative forms of validation and selection are proposed. A combined model validation and selection framework for 13C‐MFA incorporating metabolite pool size information that leverages new developments in the field is presented and advocated for. Finally, we discuss how adopting robust validation and selection procedures can enhance confidence in constraint‐based modeling as a whole and ultimately facilitate more widespread use of FBA in biotechnology.

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Sponsoring Organization:: USDOE

OSTI ID:: 2221867

Alternate ID(s):: OSTI ID: 2222500

Journal Information:: Biotechnology Progress, Journal Name: Biotechnology Progress Vol. 40 Journal Issue: 1; ISSN 8756-7938

Publisher:: Wiley Blackwell (John Wiley & Sons)Copyright Statement

Country of Publication:: United States

Language:: English

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