Isotopically Non-stationary Metabolic Flux Analysis of Heterotrophic Cell Cultures

Overview

Journal Front Plant Sci

Date 2023 Jan 26

PMID 36699846

Authors

Edward N Smith

R George Ratcliffe

Nicholas J Kruger

Affiliations

Soon will be listed here.

Abstract

Fluxes are the ultimate phenotype of metabolism and their accurate quantification is fundamental to any understanding of metabolic networks. Steady state metabolic flux analysis has been the method of choice for quantifying fluxes in heterotrophic cells, but it is unable to measure fluxes during short-lived metabolic states, such as a transient oxidative load. Isotopically non-stationary metabolic flux analysis (INST-MFA) can be performed over shorter timescales (minutes - hours) and might overcome this limitation. INST-MFA has recently been applied to photosynthesising leaves, but agriculturally important tissues such as roots and storage organs, or plants during the night are heterotrophic. Here we outline the application of INST-MFA to heterotrophic plant cells. Using INST-MFA we were able to identify changes in the fluxes supported by phosphoenolpyruvate carboxylase and malic enzyme under oxidative load, highlighting the potential of INST-MFA to measure fluxes during short-lived metabolic states. We discuss the challenges in applying INST-MFA, and highlight further development required before it can be routinely used to quantify fluxes in heterotrophic plant cells.

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References

Ma F, Jazmin L, Young J, Allen D . Isotopically nonstationary 13C flux analysis of changes in Arabidopsis thaliana leaf metabolism due to high light acclimation. Proc Natl Acad Sci U S A. 2014; 111(47):16967-72. PMC: 4250135. DOI: 10.1073/pnas.1319485111. View

Szecowka M, Heise R, Tohge T, Nunes-Nesi A, Vosloh D, Huege J . Metabolic fluxes in an illuminated Arabidopsis rosette. Plant Cell. 2013; 25(2):694-714. PMC: 3608787. DOI: 10.1105/tpc.112.106989. View

Adebiyi A, Jazmin L, Young J . 13 C flux analysis of cyanobacterial metabolism. Photosynth Res. 2014; 126(1):19-32. DOI: 10.1007/s11120-014-0045-1. View

Rossi M, Kalde M, Srisakvarakul C, Kruger N, Ratcliffe R . Cell-Type Specific Metabolic Flux Analysis: A Challenge for Metabolic Phenotyping and a Potential Solution in Plants. Metabolites. 2017; 7(4). PMC: 5746739. DOI: 10.3390/metabo7040059. View

Young J . INCA: a computational platform for isotopically non-stationary metabolic flux analysis. Bioinformatics. 2014; 30(9):1333-5. PMC: 3998137. DOI: 10.1093/bioinformatics/btu015. View

Sun X, Han G, Meng Z, Lin L, Sui N . Roles of malic enzymes in plant development and stress responses. Plant Signal Behav. 2019; 14(10):e1644596. PMC: 6768271. DOI: 10.1080/15592324.2019.1644596. View

Masakapalli S, Kruger N, Ratcliffe R . The metabolic flux phenotype of heterotrophic Arabidopsis cells reveals a complex response to changes in nitrogen supply. Plant J. 2013; 74(4):569-82. DOI: 10.1111/tpj.12142. View

Sake C, Metcalf A, Boyle N . The challenge and potential of photosynthesis: unique considerations for metabolic flux measurements in photosynthetic microorganisms. Biotechnol Lett. 2018; 41(1):35-45. PMC: 6313361. DOI: 10.1007/s10529-018-2622-4. View

Wiechert W, Noh K . Isotopically non-stationary metabolic flux analysis: complex yet highly informative. Curr Opin Biotechnol. 2013; 24(6):979-86. DOI: 10.1016/j.copbio.2013.03.024. View

10.

Sundqvist N, Grankvist N, Watrous J, Mohit J, Nilsson R, Cedersund G . Validation-based model selection for 13C metabolic flux analysis with uncertain measurement errors. PLoS Comput Biol. 2022; 18(4):e1009999. PMC: 9022838. DOI: 10.1371/journal.pcbi.1009999. View

11.

Kruger N, von Schaewen A . The oxidative pentose phosphate pathway: structure and organisation. Curr Opin Plant Biol. 2003; 6(3):236-46. DOI: 10.1016/s1369-5266(03)00039-6. View

12.

Kruger N, Masakapalli S, Ratcliffe R . Strategies for investigating the plant metabolic network with steady-state metabolic flux analysis: lessons from an Arabidopsis cell culture and other systems. J Exp Bot. 2011; 63(6):2309-23. DOI: 10.1093/jxb/err382. View

13.

Gerrard Wheeler M, Tronconi M, Drincovich M, Andreo C, Flugge U, Maurino V . A comprehensive analysis of the NADP-malic enzyme gene family of Arabidopsis. Plant Physiol. 2005; 139(1):39-51. PMC: 1203356. DOI: 10.1104/pp.105.065953. View

14.

Walsby-Tickle J, Gannon J, Hvinden I, Bardella C, Abboud M, Nazeer A . Anion-exchange chromatography mass spectrometry provides extensive coverage of primary metabolic pathways revealing altered metabolism in IDH1 mutant cells. Commun Biol. 2020; 3(1):247. PMC: 7239943. DOI: 10.1038/s42003-020-0957-6. View

15.

Knol M, Pestman W, Grobbee D . The (mis)use of overlap of confidence intervals to assess effect modification. Eur J Epidemiol. 2011; 26(4):253-4. PMC: 3088813. DOI: 10.1007/s10654-011-9563-8. View

16.

Su X, Lu W, Rabinowitz J . Metabolite Spectral Accuracy on Orbitraps. Anal Chem. 2017; 89(11):5940-5948. PMC: 5748891. DOI: 10.1021/acs.analchem.7b00396. View

17.

Agrawal S, Kumar S, Sehgal R, George S, Gupta R, Poddar S . El-MAVEN: A Fast, Robust, and User-Friendly Mass Spectrometry Data Processing Engine for Metabolomics. Methods Mol Biol. 2019; 1978:301-321. DOI: 10.1007/978-1-4939-9236-2_19. View

18.

Kruger N, Ratcliffe R . Fluxes through plant metabolic networks: measurements, predictions, insights and challenges. Biochem J. 2015; 465(1):27-38. DOI: 10.1042/BJ20140984. View

19.

Treves H, Kuken A, Arrivault S, Ishihara H, Hoppe I, Erban A . Carbon flux through photosynthesis and central carbon metabolism show distinct patterns between algae, C and C plants. Nat Plants. 2021; 8(1):78-91. PMC: 8786664. DOI: 10.1038/s41477-021-01042-5. View

20.

Chen Q, Wang B, Ding H, Zhang J, Li S . Review: The role of NADP-malic enzyme in plants under stress. Plant Sci. 2019; 281:206-212. DOI: 10.1016/j.plantsci.2019.01.010. View