Overview of Stable Isotope Metabolomics

Stable Isotope-resolved metabonomics (SIRM) is a breakthrough method combining stable isotope labeling technology with high-resolution metabonomics analysis, which can analyze the dynamic transformation path, reaction rate and network regulation mechanism of metabolites in organisms with atomic accuracy. Unlike traditional metabonomics, which only provides static "snapshots" of metabolites, SIRM has achieved a leap from "what are metabolites" to "how metabolism occurs" by tracking the spatio-temporal transfer of isotope-labeled atoms in metabolic networks, providing a new perspective for revealing the dynamic nature of life processes.

Using stable isotope labeled substrates such as [U-13C] glucose and [15N] glutamine, combined with time series sampling strategy, the transfer paths of carbon/nitrogen atoms in glycolysis, TCA cycle and nucleotide synthesis can be drawn quantitatively.Through the analysis of isotopic isomer distribution (such as the ratio of m+3 pyruvate to m+2 lactate), the activity differences of parallel metabolic branches (such as glycolysis and pentose phosphate pathway) can be distinguished. Unsteady isotope labeling model (INST-SIRM) combined with kinetic modeling can be used to calculate metabolic flux rate and turnover time of metabolites, and reveal the real-time regulation characteristics of energy metabolism, redox balance and other processes.

Integrating multi-platform data of LC-MS/MS (targeted quantification), Orbitrap HRMS (non-targeted screening) and 13C-NMR (structural analysis), an isotope labeling matrix of metabolites was constructed to realize panoramic reconstruction of metabolic network.Combined with machine learning algorithms (such as random forest and neural network), disease-specific metabolic markers and key regulatory nodes can be identified.

What is a stable isotope?

Stable isotopes refer to the isomers of elements with the same number of protons but different numbers of neutrons in the nucleus. Unlike radioactive isotopes, stable isotopes do not decay, so they can exist stably for a long time during metabolism, making them an ideal choice for tracking and quantitative analysis. Common stable isotopes include hydrogen isotope deuterium (D), carbon isotope carbon -13(13C) and nitrogen isotope nitrogen -15(15N). In the experiment of stable isotope labeling, deuterium (D) can replace hydrogen in water molecules, while carbon -13(13C) can replace carbon in food. By labeling specific molecules, we can track the flow of these labeled molecules in the metabolic network, and then reveal the synthesis and transformation process of metabolites in different organisms or cells.

Tracers are necessary for delineating metabolic pathways (Fan TW et al., 2011).

Classify

(1) stable isotope tracking metabonomics.

• Core objective: to dynamically track the biosynthesis, transformation pathway and metabolic flux of metabolites.
• Methods: Metabolic precursors (such as C-glucose and N-glutamine) labeled with stable isotopes were introduced into biological systems (cells, tissues and organisms), and the distribution of isotopes in metabolic networks was analyzed through time series, so as to analyze the dynamic changes of metabolic pathways.
• Application scenario: research on cancer metabolic reprogramming, metabolic pathway changes under the action of drugs, etc.

(2) Stable Isotope Labeling Metabolomics.

• Core objective: Isotopic labeling of metabolites by chemical or biological means to improve detection sensitivity and quantitative accuracy.
• Method: In vivo labeling: introducing labeling substrate (such as C labeling medium) into organism. In vitro labeling: isotope derivatization of the extracted metabolites (such as DANSYL labeling combined with H).
• Application scenario: quantitative analysis of low-abundance metabolites in complex samples to eliminate matrix effect in mass spectrometry detection.

(3) stable isotope assisted metabonomics analysis.

• Core objective: To analyze the structure and function of metabolic network through isotope distribution data.
• Methods: Combined with mass spectrometry (such as LC-MS, GC-MS) and nuclear magnetic resonance (NMR) techniques, isotope enrichment patterns (such as isotope isomer distribution and mass shift) were analyzed, and metabolic flux models (such as MFA based on C) were constructed.
• Application scenario: pathway optimization in metabolic engineering, mechanism research of abnormal metabolism of diseases.

Technical process

Stable isotope metabonomics can detect and identify the metabolites of biochemical reactions in vivo and accurately reflect the pathway information of glucose catabolism. The technical process of stable isotope metabonomics research on glucose catabolism regulation is basically the same, including the selection of stable isotope tracer, introduction of tracer, sample collection and processing, data analysis and metabolic pathway analysis.

Selection of stable isotope tracer

The selection of stable isotope tracer depends on the metabolic pathway studied. Glucose is the main energy source of cells and tissues (such as brain, liver, skeletal muscle, etc.) and plays an important role in glucose catabolism pathways such as glycolysis and tricarboxylic acid cycle. Therefore, glucose is a common tracer for studying glucose catabolism. At present, there are many kinds of 13C-labeled glucose on the market, among which the most commonly used tracers are [U-13C]- glucose and [1,2-13C]- glucose.

Introduction mode of stable isotope tracer

The introduction of tracer is one of the key steps in the study of stable isotope tracer metabonomics. At present, there are many common ways to introduce tracers, among which injection is the main way. There are two specific injection schemes: ① single injection: the tracer labeled with stable isotope is introduced into the body quickly at one time, which leads to a rapid increase in isotope abundance and a gradual decline after reaching the peak; ② Continuous infusion: a certain amount of stable isotope tracer is continuously infused into the body through vein at a constant rate. Continuous infusion at animal level is usually carried out through jugular vein or tail vein. In addition, stable isotope liquid diet has also become a new tracer introduction method, which avoids the influence of anesthesia and physical trauma on the experiment and can trace the deep metabolic pathway.

Sample preparation and analysis

Cell extract, blood and tissues are the main research objects of stable isotope tracer metabonomics. Because most metabolites will undergo metabolic transformation in a short time, the collected biological samples need to be inactivated by reaction. Commonly used inactivation methods include rapid freezing in liquid nitrogen, freezing at -80℃, adding organic reagents or acid-base treatment, etc. The choice of analysis platform has certain influence on sample preparation. Table 2 shows the application comparison of nuclear magnetic resonance (NMR) and mass spectrometry (MS) in stable isotope tracer metabonomics. As a common analysis platform, NMR has the following advantages: ① sample preparation is simple, and serum and urine are commonly used samples; ② Non-destructive, and the structure and properties of the sample will not be destroyed; ③ It can be quantitatively analyzed, and the signal intensity is directly proportional to the sample concentration. Compared with NMR, mass spectrometry has high selectivity and sensitivity, so it has obvious advantages in structure confirmation. In recent years, the application of mass spectrometry in stable isotope tracer metabonomics has increased year by year.

Data processing and analysis

The atlas data detected by NMR, mass spectrometry and other instruments need to be converted by software such as MestRenova and XCMS to obtain data for statistical analysis. The data processing method is determined by the analysis technology adopted and the characteristics of the application field. Whether it is NMR or mass spectrometry data, it is necessary to carry out pretreatment steps such as peak identification, peak alignment and normalization before analysis. Commonly used data analysis software includes XCMS, SIMCA-P, MAVEN, MZmine, etc., among which SIMCA-P is the most widely used. In recent years, the strategy of combining multivariate analysis with univariate analysis (such as t-test, u-test, f-test, etc.) is widely used in the analysis of stable isotope tracer metabonomics data, and the experimental data are deeply analyzed.

Metabolic pathway analysis

Stable isotope tracer metabonomics belongs to the category of metabonomics, and the relationship between signal intensity and concentration of metabolites can be obtained through isotope labeling and tracing. For the visualization of metabolic data, the structure of metabolites and the enrichment analysis of metabolic pathways, it is usually necessary to use the pathway analysis methods in traditional metabonomics. Metabolic pathway analysis is to identify the metabolic pathways involved in the concentration of metabolites by integrating data from multiple platforms and performing enrichment analysis, and to analyze and discuss these pathways emphatically. The pathway database not only contains relevant biochemical metabolic pathway information, but also includes some important notes and documents, which provide support for researchers to discover new metabolic pathways and verify known metabolic pathways. Commonly used metabolic pathway analysis platforms include human metabolomics database (HMDB), Kyoto gene and genome database (KEGG), Reactome database and Metaboanalyst software, etc. Through these tools, the target metabolic pathway can be obtained and its pathophysiological mechanism can be clarified. In addition, it can also be associated with known biological functions through databases such as HowNet and PubMed.

Application

Metabolic pathway analysis

SIRM can track the flow of metabolites by stable isotope labeling, thus helping researchers to reveal the participation of different metabolic pathways and the transformation process of metabolites. By analyzing the distribution and concentration changes of isotope-labeled metabolites in cells, researchers can deeply understand the metabolic activities of organisms under different physiological conditions.

• Metabolites of intestinal microbiota play an important role in the regulation of host health and diseases, but their metabolic interaction with host organs has not been fully explored. Mice were given 13C-inulin orally as a tracer, and the metabolites were analyzed by SIRM technology. The researchers tracked the dynamic enrichment of 13C-labeled metabolites in different organs of mice (such as plasma, liver, brain and skeletal muscle). Metabonomics analysis of U-13C-inulin showed that the plasma metabolites of treated mice changed significantly in a time-dependent manner at different time points (T6h, T12h and T24h). At T24h, the biochemical differences between the two groups were weakened. Thermographic analysis showed that T6h and T12h samples showed high levels of biochemical substances. By linear model analysis, 35 biochemical substances related to [U-13C-inulin were identified, mainly amino acids and short-chain fatty acids. In different tissues, the metabolic groups of liver, brain and skeletal muscle are obviously different, and the incorporation mode of 13C is different. For example, liver is rich in 13C5- choline and 13C3- lactic acid, while skeletal muscle shows the difference of 13C1- hydroxybutyrate, which indicates that intestinal microorganisms have an important influence on muscle ketone body production. In the brain, 13C is mainly involved in the glutamine-glutamic acid /GABA cycle. In addition, mice treated with labeled U-13C-inulin showed that choline was used to synthesize phospholipid compounds such as phosphatidylcholine (PC) and lysophosphatidylcholine (LPC), and these phospholipids also showed 13C labeling in plasma and different tissues. In the process of phospholipid synthesis, choline, as a head group, participates in lipid synthesis. These labeled lipids show different enrichment patterns in different tissues, especially in brain tissues (Xiao X et al., 2024).
• Glucose metabolism is mainly carried out through the tricarboxylic acid cycle in healthy brain, and the rest is converted into lactic acid. This process is very important to maintain the energy balance and function of the brain, and the balance of aerobic and anaerobic metabolism plays an important role in many neurodegenerative diseases, such as Alzheimer's disease, depression and schizophrenia. The role of glucose metabolism in the brain is very important for neuroscience research, but the existing methods (such as [18F]FDG PET, 13C-MRS, 2H-MRSI, etc.) have technical problems, such as the need for special hardware or expensive radioactive tracers. In order to solve this problem, the author developed QELT-MRS technology to explore brain diseases by using deuterated glucose (2H-Glc). The experimental results showed that deuterated glucose significantly affected the signal amplitudes of Glu4, Gln4 and Glc6, which decreased by 14.9%, 14.4% and 21.8% respectively. In the control experiment, 1H-Glc did not cause obvious changes, which verified the deuteration effect. Spectral analysis revealed obvious changes in deuterated glucose enrichment, especially in GABA concentration. Time-history analysis showed that the concentration of metabolites showed a decreasing trend, and there were great individual differences. CV analysis showed that the concentration changes of 14 metabolites were stable and 8 metabolites were reliable. By magnetic resonance spectroscopy (MRSI) with high time resolution, it was found that Glu4 signal decreased by 13.4% 3.5% in gray matter (GM) and 14.0% 2.9% in white matter (WM) (P = 0.0007). In the 1H-Glc experiment, all metabolites remained stable. During the 2H-Glc experiment, the attenuation trend of Glu4 is different in GM and WM, and the attenuation speed of GM is faster than that of WM. In this study, the changes of downstream metabolites (such as glutamic acid Glu) were dynamically tracked after deuterium labeled glucose (2H-Glc) was used in human body through multi-voxel 1H-MRSI sequence, thus revealing the potential of deuterium labeling in the study of brain glucose metabolism (Bednarik P et al., 2023).

Cell physiology research

By using stable isotope markers in different cell types or different environmental conditions, SIRM can track the changes of metabolic reactions in cells, help to study the physiological processes of cells such as energy metabolism, redox reaction and lipid metabolism, and then reveal the metabolic responses of cells under different stimuli.

• In the early immune reaction stage, CD8 T cells provide energy through glycolysis, and participate in nucleotide synthesis and ATP production. Glutamine enters TCA cycle, supports ATP production and participates in pyrimidine synthesis. Get 1 (glutamic acid oxaloacetic transaminase) is very important at this stage, which promotes the synthesis of aspartic acid and thus supports the proliferation of T cells. It is found that glutamine is an important fuel in oxidative metabolism of CD8 T cells, especially in vivo infection, and its contribution to TCA cycle is significantly higher than that of glucose. By injecting U-[13C] glutamine into mice, the researchers found that metabolites (such as citric acid and malic acid) in CD8 T cells were enriched with labeled carbon from glutamine, and the contribution of glutamine to TCA cycle was higher than that of glucose under the condition of infection in vivo. In addition, CD8 T cells infected with LmOVA showed higher mitochondrial membrane potential and oxidative phosphorylation (OXPHOS) activity in vivo, which indicated that glutamine supported these cells to carry out efficient energy metabolism. Glutamine not only provides an intermediate for TCA cycle through its carbon skeleton, but also provides a carbon source for cell biosynthesis, especially for the synthesis of proline and aspartic acid. By using 13C- glutamine labeling, it was found that activated CD8 T cells showed significant enrichment of glutamine-derived proline and aspartic acid in vitro and in vivo. In CD8 Teff cells in vivo, the synthesis of aspartic acid is obviously increased, and it is used for the synthesis of pyrimidine nucleotides (such as UMP and UDP- glucose). Got1 plays an important role in regulating the biosynthesis of aspartic acid. By targeting Got1 with short hairpin RNA (shRNA), it was found that the silencing of Got1 reduced the synthesis of glutamine-derived aspartic acid, resulting in the decrease of CD8 T cell proliferation. In vivo, the silence of Got1 leads to a significant decrease in the number of CD8 T cells in the immune response to LmOVA infection, suggesting that Got1 is essential for the proliferation and effector function of CD8 T cells (Ma EH et al., 2024).

Study on the interaction between plants and microorganisms

There is a close interaction between plant roots and microorganisms in soil. Through SIRM technology, researchers can track the metabolic process of plant root exudates and how these metabolites affect the structure and function of microbial communities.

• The effects of root exudation, microbial assimilation, decomposition and soil biota on nitrogen transfer were studied by using 15N labeled white clover roots. The results showed that the biomass of clover buds under 15N- urea treatment was significantly lower than that of the control (p < 0.01), but there was no significant difference among other treatments. The root biomass of clover increased significantly in 15N- urea and exudation treatments (p < 0.01), but there was no significant difference among other treatments. The biomass of Lolium perenne was significantly higher than that of the control, and it performed better in other treatments, although these differences were not significant. Except aseptic treatment, all treatments reduced nodule abundance, especially the 15N- urea, defoliation and fungal treatment groups, which showed a significant decrease (p < 0.05). There was no significant difference in the retention rate of 15N in clover buds among different treatments, but the decomposition treatment showed the largest nitrogen transfer, about 9.3% of the nitrogen in ryegrass came from clover buds, and the nitrogen transfer in other treatments (such as aseptic, 15N- urea, defoliation, etc.) was low, and the nitrogen transfer in the exudation treatment was the smallest. The nitrogen transfer of clover in the decomposition treatment was significantly higher than that of other treatments, and the protein pool of soil microorganisms also showed significant differences, especially in the decomposition treatment, the proportion of nitrogen derived from clover was higher. 15N- urea treatment significantly increased the biomass of clover, but had no significant effect on the biomass change of ryegrass. The amino acid exudation of clover is higher than that of ryegrass, and the amino acid composition is different. In the experiment of clover to ryegrass, the 15N retention of clover was 41.7%, while that of clover to clover was 72.6%. The amount of nitrogen transfer is similar in the two transfer directions, but the proportion of donor-derived nitrogen in soil is small. Amino acid incorporation in different plants is different, and root exudates affect nitrogen assimilation pathway. Generally speaking, soil microbial community, turf management history and interaction between plants and insects have a profound impact on nitrogen transfer (Reay MK et al., 2022).

The response of plants to environmental stress

When plants respond to external environmental changes (such as drought, salinity, pests and diseases, etc.), their metabolism will change. SIRM technology can track the metabolic response of plants under stress conditions by stable isotope labeling.

• The results show that asymmetric warming of temperature (that is, nighttime warming in winter and spring) has significant effects on root growth, nitrogen absorption and nitrogen fate of winter wheat. By using 15N labeled fertilizer, the absorption, residue and loss of fertilizer under different warming conditions were studied and observed. The results show that warming at night is helpful to improve the recovery rate of fertilizer and reduce the loss of fertilizer. Especially, the nighttime warming in winter+spring (WSW treatment) significantly increased the root biomass, and the root/bud ratio at jointing, flowering and maturity also increased. The accumulation rate of root dry matter and nitrogen uptake of winter wheat during jointing to flowering were significantly increased by warming treatment, especially under WSW treatment. In addition, warming at night also reduced the residual fertilizer 15N content in the soil, especially WSW treatment, which significantly reduced the fertilizer loss. Path analysis shows that the root biomass in 0-20 cm soil layer is very important to reduce the loss of 15N, especially in flowering period. Night warming treatment also significantly increased the yield of wheat, and WSW treatment increased the yield the most, reaching 10.62%-12.39%. On the whole, the winter and spring nighttime warming significantly increased wheat yield by increasing root biomass, increasing nitrogen recovery rate and reducing nitrogen loss. It is suggested that under the background of climate change, effective nitrogen management strategies should be formulated according to these findings to improve the nitrogen use efficiency of wheat and reduce the loss of nitrogen in the environment(Hu C et al., 2019).

Nutrition and disease monitoring

SIRM is also widely used in nutrition research, tracking its metabolism in vivo through isotope-labeled nutrients, and studying the absorption, metabolism and excretion process of food. In addition, it can also be applied to the study of metabolic diseases (such as diabetes and obesity) to help reveal the mechanism of metabolic disorder.

• Hepatocellular carcinoma (HCC) is an aggressive malignant tumor, and early detection and treatment still face many challenges. It is found that the reprogramming of fructose metabolism in hepatocellular carcinoma may change glycolytic pathway, and fructose is converted into lactic acid instead of the traditional ketokinase pathway. Based on this discovery, the researchers evaluated the potential of [6,6'-2H2] fructose as a metabolic probe and compared it with [6,6'-2H2] glucose. The metabolic processes of [6,6'-2H2] fructose and [6,6'-2H2] glucose in HepG2 cells were studied by using 2H NMR technique. By analyzing the metabolites in cell culture medium, it was found that the labeled metabolites such as lactic acid, glutamic acid/glutamine and alanine had obvious signals in NMR spectrum, and the lactic acid signal was broadened by 2H substitution. The resolution was further improved by 2H decoupling technology. Time series experiments show that the signal of metabolites gradually increases with time, revealing the conversion rate of metabolites during glycolysis. In vivo, the metabolic process was monitored by subcutaneous HepG2 mouse model. The results showed that the precursor was almost completely metabolized within about 60 minutes, and the deuterated labeling signal increased significantly with time. The concentration of metabolites was quantitatively analyzed by the change of HDO peak. The HDO production rates of glucose and fructose in tumor at 2 hours were 35 14 mm/h and 36 12 mm/h, respectively. The conversion rate of glucose to lactic acid was 12.7 2.2 mm/h, while fructose was 6.4 0.9 mm/h.. 2H glucose and 2H fructose were rapidly distributed to the whole body and tumor tissues, and the conversion rate of glucose to HDO was higher than that of fructose, and the HDO signal was significantly enhanced in liver tumors and surrounding tissues. In normal liver, the process of transforming fructose and glucose into HDO in 2 hours is similar, but no lactic acid signal was observed, suggesting that anaerobic metabolism in tumor tissue is enhanced. By tracing TCA cycle activity with 2H markers, it is found that HDO production is related to metabolic activity in liver and liver tumors, and it is speculated that HDO production can simplify the method of evaluating fructose intake in liver for 2H. In the future, DMI and hyperpolarized 13C MRI can be combined to explore the glycolysis of liver and the metabolic pathway of tumor. Developing 2H labeled fructose as a new DMI reagent will provide a new idea for early diagnosis and treatment of liver disease (Zhang G et al., 2023).

References

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