Local circulation of elites punctuated by transregional mobility enabled steppe political consolidation in the Xiongnu nomadic state.

The Xiongnu polity (ca. 200 BC- 150 AD) emerged out of indigenous community-centered socio-political structures to forge a powerful state that commanded the Mongolian steppe and beyond. Underpinned by a highly mobile pastoralist population, accustomed to seasonally rhythmic moves and embedded in an equestrian culture that facilitated rapid transport over long-distances, it remains unclear precisely how the movement of commoners, local aristocrats and regional elites abetted the formation and organization of Xiongnu state structures. Here, we evaluate Xiongnu movement and dietary intake through multi-stable isotopic analyses of tooth enamel from directly dated Xiongnu intermediate elites recovered from the mortuary center of Baga Gazaryn Chuluu-a prominent granite outcrop set in the Gobi Desert. Carbon isotope (δ13C) analysis indicates millet was consumed by some individuals, but whether or not this C4 cultivar contributed to the diets of most elites remains ambiguous in this C3/C4 desert-steppe environment. The effectiveness of oxygen isotopes (δ18O) to establish mobility appears much reduced in steppe environments, where geospatially sensitive information appears disrupted by extraordinary seasonality in meteoric water oxygen isotopes, pronounced oxygen isotopic variation in potential drinking water sources, and culturally mediated drinking practices. Most revealing, strontium isotopes (87Sr/86Sr) indicate circulation of local elites around this central place and beyond, a mobility format that helped leaders cement their own position through political consolidation of spatially dispersed mobile pastoralist communities. The consistent presence at Baga Gazaryn Chuluu of extra-local intermediate elites also points toward the importance of transregional mobility in binding together the Xiongnu polity over the vast distances of the eastern steppe.

In situ monitoring of the shikimate pathway: a combinatorial approach of Raman reverse stable isotope probing and hyperspectral imaging.

Sensing and visualization of metabolites and metabolic pathways in situ are significant requirements for tracking their spatiotemporal dynamics in a non-destructive manner. The shikimate pathway is an important cellular mechanism that leads to the de novo synthesis of many compounds containing aromatic rings of high importance such as phenylalanine, tyrosine, and tryptophan. In this work, we present a cost-effective and extraction-free method based on the principles of stable isotope-coupled Raman spectroscopy and hyperspectral Raman imaging to monitor and visualize the activity of the shikimate pathway. We also demonstrated the applicability of this approach for nascent aromatic amino acid localization and tracking turnover dynamics in both prokaryotic and eukaryotic model systems. This method can emerge as a promising tool for both qualitative and semi-quantitative in situ metabolomics, contributing to a better understanding of aromatic ring-containing metabolite dynamics across various organisms.

Carbon 14 and Carbon 13 Syntheses of Velagliflozin.

Velagliflozin is the active ingredient of the first oral liquid medication approved by the Food and Drug Administration for the treatment of diabetes in cats. This compound belongs to the known class of sodium-glucose cotransporter 2 inhibitors approved to treat diabetes in human. Here, we report the detailed synthesis of velagliflozin labeled with carbon 14 and carbon 13.

SIMPEL: using stable isotopes to elucidate dynamics of context specific metabolism.

The capacity to leverage high resolution mass spectrometry (HRMS) with transient isotope labeling experiments is an untapped opportunity to derive insights on context-specific metabolism, that is difficult to assess quantitatively. Tools are needed to comprehensively mine isotopologue information in an automated, high-throughput way without errors. We describe a tool, Stable Isotope-assisted Metabolomics for Pathway Elucidation (SIMPEL), to simplify analysis and interpretation of isotope-enriched HRMS datasets. The efficacy of SIMPEL is demonstrated through examples of central carbon and lipid metabolism. In the first description, a dual-isotope labeling experiment is paired with SIMPEL and isotopically nonstationary metabolic flux analysis (INST-MFA) to resolve fluxes in central metabolism that would be otherwise challenging to quantify. In the second example, SIMPEL was paired with HRMS-based lipidomics data to describe lipid metabolism based on a single labeling experiment. Available as an R package, SIMPEL extends metabolomics analyses to include isotopologue signatures necessary to quantify metabolic flux.

Carbon and Oxygen Isotopic Ratio Analysis by FT ICR MS for Natural Vanillin Authentication.

Vanillin is the main component of vanilla flavor and is naturally produced from an orchid. However, due to the high cost and time-intensive nature of cultivating natural vanilla pods, most of the vanillin is mainly artificially manufactured. Existing methodologies, such as isotope ratio mass spectrometry (IRMS) and site-specific natural isotopic fractionation by nuclear magnetic resonance (SNIF-NMR), are employed to differentiate natural vanillin from other sources based on carbon and hydrogen isotope measurements. Nevertheless, these methods have limitations, as the carbon isotopic ratio can be counterfeited by adding commercially available enriched vanillin. For this research, we purified 1 mg of vanillin from pods from various geographical and botanical sources. We developed a novel method for analyzing 13C/12C and 18O/16O isotopic ratios of vanillin using direct injection analysis coupled with Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS). This innovative approach enables the examination of bulk vanillin carbon and oxygen isotopic ratios, as well as specific molecular fragments. By analyzing a characteristic vanillin fragment that provides site-specific 18O/16O isotopic ratio data, we achieved superior clustering and discrimination of samples based on their botanical source and geographical origin. Our proposed method holds significant potential for vanillin authentication and can be performed using a mere 20 µg of pure vanillin in just 10 min of analysis time. Subsequent research should focus on acquiring additional vanillin samples from diverse botanical, geographical, and biosynthetic origins while exploring various isotopic ratios to further enhance the reproducibility and reliability of this methodology.

Quantification and isotope abundance determination of 13C labeled intracellular sugar metabolites with hydrophilic interaction liquid chromatography.

Metabolic flux analysis (MFA) using stable isotope labeled tracers is a powerful tool to estimate fluxes through metabolic pathways. It finds applications in studying metabolic changes in diseases, regulation of cellular energetics, and novel strategies for metabolic engineering. Accurate and precise quantification of the concentration of metabolites and their labeling states is critical for correct MFA results. Utilizing an ultra-high performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS) system, an analytical method for simultaneously quantifying the concentration of sugar metabolites and their mass isotopologue distribution (MID) was developed. The method performs with good linearity and coefficient of determination (R2) > 0.99, while the detection limit ranged from 0.1 to 50 mg L-1. Seven sugar metabolites were detected in a labeled Brevibacterium flavum sample using the method. The detected quantities ranged from 6.15 to 3704.21 mg L-1, and 13C abundance was between 12.77% and 66.67% in the fermentation fluid and 16.28% and 91.93% in the bacterial body. Overall, the method is efficient, accurate, and suitable for analysis of labeled sugar metabolites in 13C MFA studies.

Stable isotope synthesis of glycine transporter 1 inhibitor Iclepertin (BI 425809) and its major metabolites.

Stable isotope labeled Iclepertin (BI 425809, 1) and its major metabolites are needed as internal standards in bioanalytical studies. BI 425809 consists of two main building blocks, 5-methylsulfonyl-2-[(1R)-2,2,2-trifluoro-1-methyl-ethoxy]benzoic acid (2) and 3-[(1R,5R)-3-azabicyclo[3.1.0]hexan-5-yl]-5-(trifluoromethyl)isoxazole (3) linked to each other via an amide bond. We used fluoro[13 C6 ]benzene as the starting material in the preparation of [13 C6 ]-2. This intermediate was then employed to access carbon 13 labeled Iclepertin ([13 C6 ]-1) and other metabolites. The major metabolite BI 761036 (6), which resulted from cytochrome P450 oxidation and amide hydrolysis of BI 425809, was prepared labeled with carbon 13 and nitrogen 15 via two synthetic routes. In the first route, diethyl [13 C3 ]malonate, [13 C]methyl iodide, and hydroxyl[15 N]amine were used to provide [13 C4 ,15 N]-BI 761036 ([13 C4 ,15 N]-6a) in 13 steps in 6% overall yield, whereas in the second route, [13 C3 ]propargyl alcohol, potassium [13 C]cyanide, and [15 N]ammonia were used to furnish [13 C4 ,15 N]-BI 761036 ([13 C4 ,15 N]-6b) in 11 steps in 1% overall yield. The detailed stable isotope synthesis of 1 and its major metabolites is described.

FreeFlux: A Python Package for Time-Efficient Isotopically Nonstationary Metabolic Flux Analysis.

13C metabolic flux analysis is a powerful tool for metabolism characterization in metabolic engineering and synthetic biology. However, the widespread adoption of this tool is hindered by limited software availability and computational efficiency. Currently, the most widely accepted 13C-flux tools, such as INCA and 13CFLUX2, are developed in a closed-source environment. While several open-source packages or software are available, they are either computationally inefficient or only suitable for flux estimation at isotopic steady state. To address the need for a time-efficient computational tool for the more complicated flux analysis at an isotopically nonstationary state, especially for understanding the single-carbon substrate metabolism, we present FreeFlux. FreeFlux is an open-source Python package that performs labeling pattern simulation and flux analysis at both isotopic steady state and transient state, enabling a more comprehensive analysis of cellular metabolism. FreeFlux provides a set of interfaces to manipulate the objects abstracted from a labeling experiment and computational process, making it easy to integrate into other programs or pipelines. The flux estimation by FreeFlux is fast and reliable, and its validity has been confirmed by comparison with results from other computational tools using both synthetic and experimental data. FreeFlux is freely available at https://github.com/Chaowu88/freeflux with a detailed online tutorial and documentation provided at https://freeflux.readthedocs.io/en/latest/index.html.

Advantages of using biologically generated 13C-labelled multiple internal standards for stable isotope-assisted LC-MS-based lipidomics.

In comprehensive lipidomics studies, accurate quantification is essential but biological and/or clinical relevance is often hindered due to unwanted variations such as lipid degradation during sample preparation, matrix effects and non-linear responses of analytical instruments. In addition, the wide chemical diversity of lipids can complicate the accurate identification of individual lipids. These analytical limitations can potentially be corrected efficiently by the use of lipid-specific isotopically labelled internal standards (IS) but currently such IS mixtures have limited coverage of the mammalian lipidome. In this study, an in vivo13C labelling strategy was employed to explore four species (Escherichia coli, Arthrospira platensis, Saccharomyces cerevisiae and Pichia pastoris) as a source of 13C-labelled internal standards (13C-ISs) for more accurate and quantitative liquid chromatography (LC)-mass spectrometry (MS)-based lipidomics. Results showed that extracts from 13C-labelled P. pastoris and S. cerevisiae contain the highest percentage of uniformly labelled lipids (both 83% compared to 67% and 69% in A. platensis and E. coli, respectively) and 13C-labelled P. pastoris extract was identified as the optimum source of 13C-ISs for comprehensive data normalisation to correct unwanted variations during sample preparation and LC-MS analysis. Overall, use of a biologically generated 13C-IS lipid mixture of 357 identified lipid ions resulted in significant reduction in the lipid CV% of normalisation compared with other normalisation methods using total ion counts or a commercially available deuterated internal standard mixture. This improved normalisation using 13C-IS was confirmed in a typical lipidomics analysis using a large number of samples (>100+) and long analysis time (>70 h). This study highlights the benefit of an in vivo labelling strategy for reducing technical and analytical variations introduced during sample preparation and analysis in lipidomics studies.

13C Isotope Labeling and Mass Spectrometric Isotope Enrichment Analysis in Acute Brain Slices.

Feeding of stable 13C-labeled compounds coupled to mass spectrometric analysis has enabled the characterization of dynamic metabolite partitioning in various experimental conditions. This information is particularly relevant for the study and functional understanding of brain metabolic heterogeneity. We here describe a protocol for the analysis of metabolic enrichment analysis upon feeding of murine acute cerebellar slices with 13C-labeled substrates.

Tracer or toxicant: Does stable isotope labeling affect central processes in aquatic food webs?

Stable isotope analysis (SIA) is an elementary technique in food web ecology, but its insights become increasingly ambiguous in complex systems. One approach to elevate the utility of SIA in such systems is the use of heavy isotope tracers (i.e., labeling). However, the fundamental assumption that the addition of such tracers does not affect in situ conditions has been challenged. This study tests if labeling is suitable for autotrophy-based and detritus-based aquatic food webs. For the former, the survival and reproduction of Daphnia magna fed with phytoplankton cultured at different levels of 15N addition were assessed. For the latter, the microbial decomposition of leaf litter was assessed at the same tracer levels. While no significant differences were observed, effect patterns were comparable to a previous study, supporting the isotopic redundancy hypothesis that postulates discrete quantum mechanical states at which the reaction speeds of metabolic processes are altered. Although physiology (reproduction) and activity (microbial decomposition) might not be altered to an ecologically significant level, labeling with heavy stable isotopes could potentially affect isotopic fractionation in biochemical processes and bias conclusions drawn from resulting SI ratios.

Reconstruction of Glutathione Metabolism in the Neuronal Model of Rotenone-Induced Neurodegeneration Using Mass Isotopologue Analysis with Hydrophilic Interaction Liquid Chromatography-Zeno High-Resolution Multiple Reaction Monitoring.

Accurate reconstruction of metabolic pathways is an important prerequisite for interpreting metabolomics changes and understanding the diverse biological processes in disease models. A tracer-based metabolomics strategy utilizes stable isotope-labeled precursors to resolve complex pathways by tracing the labeled atom(s) to downstream metabolites through enzymatic reactions. Isotope enrichment analysis is informative and achieved by counting total labeled atoms and acquiring the mass isotopologue distribution (MID) of the intact metabolite. However, quantitative analysis of labeled metabolite substructures/moieties (MS2 fragments) can offer more valuable insights into the reaction connections through measuring metabolite transformation. In order to acquire the isotopic labeling information at the intact metabolite and moiety level simultaneously, we developed a method that couples hydrophilic interaction liquid chromatography (HILIC) with Zeno trap-enabled high-resolution multiple reaction monitoring (MRMHR). The method enabled accurate and reproducible MID quantification for intact metabolites as well as their fragmented moieties, with notably high sensitivity in the MS2 fragmentation mode based on the measurement of 13C- or 15N-labeled cellular samples. The method was applied to human-induced pluripotent stem cell-derived neurons to trace the fate of 13C/15N atoms from D-13C6-glucose/L-15N2-glutamine added to the media. With the MID analysis of both intact metabolites and fragmented moieties, we validated the pathway reconstruction of de novo glutathione synthesis in mid-brain neurons. We discovered increased glutathione oxidization from both basal and newly synthesized glutathione pools under neuronal oxidative stress. Furthermore, the significantly decreased de novo glutathione synthesis was investigated and associated with altered activities of several key enzymes, as evidenced by suppressed glutamate supply via glucose metabolism and a diminished flux of glutathione synthetic reaction in the neuronal model of rotenone-induced neurodegeneration.

Metabolite profiling and identification in living cells by coupling stable isotope tracing and induced electrospray mass spectrometry.

Direct observation of metabolites in living cells by mass spectrometry offers a bright future for biological studies but also suffers a severe challenge to untargeted peak assignment to tentative metabolite candidates. In this study, we developed a method combining stable isotope tracing and induced electrospray mass spectrometry for living-cells metabolite measurement and identification. By using 13C6-glucose and ammonium chloride-15N as the sole carbon and nitrogen sources for cell culture, Escherichia coli synthesized metabolites with 15N and 13C elements. Tracing the number of carbon and nitrogen atoms could offer a complementary dimension for candidate peak searching. As a result, the identification confidence of metabolites achieved a universal improvement based on carbon/nitrogen labelling and filtration.

DNA-, RNA-, and Protein-Based Stable-Isotope Probing for High-Throughput Biomarker Analysis of Active Microorganisms.

Stable-isotope probing (SIP) enables researchers to target active populations within complex microbial communities, which is achieved by providing growth substrates enriched in heavy isotopes, usually in the form of 13C, 18O, or 15N. After growth on the substrate and subsequent extraction of microbial biomarkers, typically nucleic acids or proteins, the SIP technique is used for the recovery and analysis of isotope-labelled biomarkers from active microbial populations. In the years following the initial development of DNA- and RNA-based SIP, it was common practice to characterize labelled populations by targeted gene analysis. Such approaches usually involved fingerprint-based analyses or sequencing clone libraries containing 16S rRNA genes or functional marker gene amplicons. Although molecular fingerprinting remains a valuable approach for rapid confirmation of isotope labelling, recent advances in sequencing technology mean that it is possible to obtain affordable and comprehensive amplicon profiles, or even metagenomes and metatranscriptomes from SIP experiments. Not only can the abundance of microbial groups be inferred from metagenomes, but researchers can bin, assemble, and explore individual genomes to build hypotheses about the metabolic capabilities of labelled microorganisms. Analysis of labelled mRNA is a more recent advance that can provide independent metatranscriptome-based analysis of active microorganisms. The power of metatranscriptomics is that mRNA abundance often correlates closely with the corresponding activity of encoded enzymes, thus providing insight into microbial metabolism at the time of sampling. Together, these advances have improved the sensitivity of SIP methods and allowed using labelled substrates at environmentally relevant concentrations. Particularly as methods improve and costs continue to drop, we expect that the integration of SIP with multiple omics-based methods will become prevalent components of microbial ecology studies, leading to further breakthroughs in our understanding of novel microbial populations and elucidation of the metabolic function of complex microbial communities. In this chapter, we provide protocols for obtaining labelled DNA, RNA, and proteins that can be used for downstream omics-based analyses.

Recent progress in analysis of intermediary metabolism by ex vivo 13 C NMR.

Advanced imaging technologies, large-scale metabolomics, and the measurement of gene transcripts or enzyme expression all enable investigations of intermediary metabolism in human patients. Complementary information about fluxes in individual metabolic pathways may be obtained by ex vivo 13 C NMR of blood or tissue biopsies. Simple molecules such as 13 C-labeled glucose are readily administered to patients prior to surgical biopsies, and 13 C-labeled glycerol is easily administered orally to outpatients. Here, we review recent progress in practical applications of 13 C NMR to study cancer biology, the response to oxidative stress, gluconeogenesis, triglyceride synthesis in patients, as well as new insights into compartmentation of metabolism in the cytosol. The technical aspects of obtaining the sample, preparing material for analysis, and acquiring the spectra are relatively simple. This approach enables convenient, valuable, and quantitative insights into intermediary metabolism in patients.

Analysis of the Amine Submetabolome Using Novel Isotope-Coded Pyrylium Salt Derivatization and LC-MS: Herbs and Cancer Tissues as Cases.

The amine submetabolome, including amino acids (AAs) and biogenic amines (BAs), is a class of small molecular compounds exhibiting important physiological activities. Here, a new pyrylium salt named 6,7-dimethoxy-3-methyl isochromenylium tetrafluoroborate ([d0]-DMMIC) with stable isotope-labeled reagents ([d3]-/[d6]-DMMIC) was designed and synthesized for amino compounds. [d0]-/[d3]-/[d6]-DMMIC-derivatized had a charged tag and formed a set of molecular ions with an increase of 3.02 m/z and the characteristic fragment ions of m/z 204.1:207.1:210.1. When DMMIC coupled with liquid chromatography-mass spectrometry (LC-MS), a systematic methodology evaluation for quantitation proved to have good linearity (R2 between 0.9904 and 0.9998), precision (interday: 2.2-21.9%; intraday: 1.0-19.7%), and accuracy (recovery: 71.8-108.8%) through the test AAs. Finally, the methods based on DMMIC and LC-MS demonstrated the advantaged application by the nontargeted screening of BAs in a common medicinal herb Senecio scandens and an analysis of metabolic differences among the amine submetabolomes between the carcinoma and paracarcinoma tissues of esophageal squamous cell carcinoma (ESCC). A total of 20 BA candidates were discovered in S. scandens as well as the finding of 13 amine metabolites might be the highest-potential differential metabolites in ESCC. The results showed the ability of DMMIC coupled with LC-MS to analyze the amine submetabolome in herbs and clinical tissues.

Ultrahigh resolution MS1/MS2-based reconstruction of metabolic networks in mammalian cells reveals changes for selenite and arsenite action.

Metabolic networks are complex, intersecting, and composed of numerous enzyme-catalyzed biochemical reactions that transfer various molecular moieties among metabolites. Thus, robust reconstruction of metabolic networks requires metabolite moieties to be tracked, which cannot be readily achieved with mass spectrometry (MS) alone. We previously developed an Ion Chromatography-ultrahigh resolution-MS1/data independent-MS2 method to track the simultaneous incorporation of the heavy isotopes 13C and 15N into the moieties of purine/pyrimidine nucleotides in mammalian cells. Ultrahigh resolution-MS1 resolves and counts multiple tracer atoms in intact metabolites, while data independent-tandem MS (MS2) determines isotopic enrichment in their moieties without concern for the numerous mass isotopologue source ions to be fragmented. Together, they enabled rigorous MS-based reconstruction of metabolic networks at specific enzyme levels. We have expanded this approach to trace the labeled atom fate of [13C6]-glucose in 3D A549 spheroids in response to the anticancer agent selenite and that of [13C5,15N2]-glutamine in 2D BEAS-2B cells in response to arsenite transformation. We deduced altered activities of specific enzymes in the Krebs cycle, pentose phosphate pathway, gluconeogenesis, and UDP-GlcNAc synthesis pathways elicited by the stressors. These metabolic details help elucidate the resistance mechanism of 3D versus 2D A549 cultures to selenite and metabolic reprogramming that can mediate the transformation of BEAS-2B cells by arsenite.

Novel Nuclear Magnetic Resonance Method for Position-Specific Carbon Isotope Analysis of Organic Molecules with Significant Impurities.

We introduce a novel nuclear magnetic resonance (NMR) tool for determining position-specific carbon (13C/12C) isotope ratios within complex organic molecules. This analytical advancement allows us to measure position-specific isotope ratios of samples that contain impurities with NMR peaks that overlap with the signals of interest. The method involves collecting a series of alternating 13C-coupled and 13C-decoupled 1H NMR spectra using an NMR pulse sequence designed to optimize temperature stability, followed by a data reduction scheme that allows the signals of interest to be isolated from signals of impurities. The method was validated using glycine reference materials with known 13C/12C ratios from the US Geological Survey (USGS) into which impurities typically found in amino acid samples were intentionally introduced. Following validation, the method was used to determine position-specific 13C/12C ratios in a set of USGS l-valine materials (USGS73, -74, -75) that contain significant impurities associated with their biological origin. The l-valines were found to contain distinct intramolecular isotope variability, and the 13Cα isotope spikes in USGS74 and USGS75 were clearly detected, where they preserve carbon isotope ratios of -4.8 ± 0.9‰ and +11.5 ± 0.8‰, respectively. Carbon isotope abundance at the beta and gamma positions indicates that the USGS73 l-valine was obtained from a different source than USGS74 and -75. This analytical approach is a significant step forward in the field of position-specific isotope analysis at natural abundance via NMR because it enables the investigation of samples that contain impurities which are typically present in samples derived from natural sources.

Stable isotope ratio analysis of carbon to distinguish sialic acid from freshly stewed bird's nest products.

Freshly stewed bird's nest products are easily adulterated with exogenous synthetic sialic acid to enhance the grade of the products and sell at high prices. This paper identifies the carbon stable isotope characteristics of sialic acid from natural and commercially synthetic sources using stable isotope ratio mass spectrometry (IRMS). Specifically, an off-line pretreatment technique combined with on-line LC-IRMS was developed to accurately determine δ13C values of sialic acid in a freshly stewed bird's nest. This method has no obvious isotope fractionation and good reproducibility. EA-IRMS was used to determine the δ13C values of commercial sialic acid. The results showed that the δ13C values of sialic acid from natural and synthetic sources were -29.90% ± 0.42% and -16.26% ± 3.91%, respectively, with distinct carbon stable isotope distribution characteristics. By defining a δ13C threshold value of -28.54% for natural SA, additional commercial SA from a minimum of 10% can be identified. Therefore, δ13C was proposed as a suitable tool for verifying the authenticity of fresh stewed bird's nests on the market.

[Construction and application of natural stable isotope correction matrix in 13C-labeled metabolic flux analysis].

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.