¹³C metabolic flux analysis (¹³C-MFA) enables the precise quantification of intracellular metabolic reaction rates by analyzing the distribution of mass isotopomers of proteinogenic amino acids or intracellular metabolites through ¹³C labeling experiments. ¹³C-MFA has received much attention as it can help systematically understand cellular metabolic characteristics, guide metabolic engineering design and gain mechanistic insights into pathophysiology. This article reviews the advances of ¹³C-MFA in the past 30 years and discusses its potential and future perspective, with a focus on its application in industrial biotechnology and biomedicine.
Amino Acids ; Carbon Isotopes ; Isotope Labeling ; Metabolic Engineering ; Metabolic Flux Analysis ; Models, Biological

Stable isotope ¹³C labeling is an important tool to analyze cellular metabolic flux. The ¹³C distribution in intracellular metabolites can be detected via mass spectrometry and used as a constraint in intracellular metabolic flux calculations. Then, metabolic flux analysis algorithms can be employed to obtain the flux distribution in the corresponding metabolic reaction network. However, in addition to carbon, other elements such as oxygen in the nature also have natural stable isotopes (e.g., ¹⁷O, ¹⁸O). This makes the isotopic information of elements other than the ¹³C marker interspersed in the isotopic distribution measured by the mass spectrometry, especially that of the molecules containing many other elements, which leads to large errors. Therefore, it is essential to correct the mass spectrometry data before performing metabolic flux calculations. In this paper, we proposed a method for construction of correction matrix based on Python language for correcting the measurement errors due to natural isotope distribution. The method employed a basic power method for constructing the correction matrix with simple structure and easy coding implementation, which can be directly applied to data pre-processing in ¹³C metabolic flux analysis. The correction method was then applied to the intracellular metabolic flux analysis of ¹³C-labeled Aspergillus niger. The results showed that the proposed method was accurate and effective, which can serve as a reliable data correction method for accurate microbial intracellular metabolic flux analysis.
Metabolic Flux Analysis ; Isotope Labeling/methods* ; Carbon Isotopes/metabolism* ; Mass Spectrometry/methods* ; Metabolic Networks and Pathways

this report describes the structures of high-mannose-type N-linked oligosaccharides in glycoproteins synthesized by the microfilariae of Dirofioria immitis. Microfilariae of D. immitis were incubated in vitro in media contaning 2-[(3)H] mannose to allow metabolic radiolabeling of the oligosaccharide moieties of newly synthesized glycoproteins. Glycopeptides were prepared from the radiolabeled glycoproteins by digestion with pronase and fractionation by chromatography on concanavalin A-Sepharose. Thirty eight percent of 2-[(3)H] mannose incorporated into the microfilariae of D. immitis glycopeptides was recovered in high mannose-type asparagine-linked oligosaccharides whech were bound to the immobilized lectin. Upon treatment of 2-[(3)H] mannose labeled glycopeptides with endo-beta-N-acetylglucosaminidase H, the high mannose-type chains were released and their structures were determined by high performance liquid chromatography and exoglycosidase digestion. The major species of high mannose-type chains synthesized by microfilariae of D. immitis have the composition Man(5) GlcNAc(2), Man(6) ClcNAc(2), Man(8) GlcNA(2), and Man(8) GlcNAc(2). Structural analyses indicate that these oligosaccharides are similar to high mannose-type chains synthesized by vertebrates.
parasitology-helminth-nematoda ; Dirofilaria immitis ; mannose ; carbohydrates ; oligosaccharieds ; micrlfilariae ; metabolic labeling ; HPLC ; enzyme digestion ; biochemistry

Intracellular metabolic fluxes are important to understand metabolic characteristics of cells and to direct metabolic engineering strategies. Because intracellular fluxes cannot be directly assessed, isotope experiments are usually conducted to trace metabolic fluxes. The flux-ratio analysis can reflect high biochemical veracity, be employed to identify the topology of the networks, and offer greatly reduced computational expense for flux determination. In order to apply this metabolic analysis method to better elucidate more cell systems, we discussed in this study the principles, experiments and assays, data interpretation, and other issues that should be considered in flux ratio determination, metabolic flux quantification and its metabolic engineering applications.
Carbon Isotopes ; Cells ; metabolism ; Genetic Engineering ; Humans ; Isotope Labeling ; Metabolic Networks and Pathways ; Metabolism ; Spectrum Analysis