Pseudotargeted Metabolomics Method Research Articles

A pseudo-targeted metabolomics for discovery of potential biomarkers of cardiac hypertrophy in rats

Cardiac hypertrophy (CH) is one of the stages in the occurrence and development of severe cardiovascular diseases, and exploring its biomarkers is beneficial for delaying the progression of severe cardiovascular diseases. In this research, we established a comprehensive and highly efficient pseudotargeted metabolomics method, which demonstrated a superior capacity to identify differential metabolites when compared to traditionaluntargeted metabolomics. The intra/inter-day precision and reproducibility results proved the method is reliable and precise. The established method was then applied to seek the potential differentiated metabolic biomarkers of cardiac hypertrophy (CH) rats, and oxylipins, phosphorylcholine (PC), lysophosphatidylcholine (LysoPC), lysophosphatidylethanolamine (LysoPE), Krebs cycle intermediates, carnitines, amino acids, and bile acids were disclosed to be the possible differentiate components. Their metabolic pathway analysis revealed that the potential metabolic alterations in CH rats were mainly associated with phenylalanine, tyrosine and tryptophan biosynthesis, phenylalanine metabolism, arachidonic acid metabolism, citrate cycle, glyoxylate and dicarboxylate metabolism, and tyrosine metabolism. In sum, this research provided a comprehensiveand reliable LC-MS/MS MRM platform for pseudo-targeted metabolomics investigation of disease condition, and some interesting potential biomarkers were disclosed for CH, which merit further exploration in the future.

Mass spectrometry-based pseudotargeted metabolomics reveals metabolic variations in a2-induced gastric cancer cell.

Gastric cancer (GC) is one of the most malignant tumors with high morbidity and mortality in the world. Compound a2, a Jiyuan oridonin derivative, exhibited excellent anti-proliferative activity against GC cells. To investigate the gastric cellular response to a2 therapy as a novel drug candidate, we adopted a pseudotargeted metabolomics method to explore metabolic variation in a2-induced MGC-803 gastric cells using liquid chromatography tandem mass spectrometry combined with multivariate statistical analysis. The results showed that a2 treatment induced significant metabolic changes in the levels of aminoacyl-tRNA biosynthesis, alanine, aspartate and glutamate metabolism, pyrimidine metabolism, and tricarboxylic acid cycle, approximately 80% of the metabolites were down-regulated in the low-dose and high-dose groups including aspartate, tryptophan, sedoheptulose 7-phosphate, succinate, 2'-deoxyadenosine, uridine, cytidine, etc. which can provide evidence for a new therapy of GC.

Pseudotargeted metabolomics method and its application in erastin-stimulated gastric adenocarcinoma cells based on liquid chromatography with tandem mass spectrometry

Erastin, a classical ferroptosis inducer, exerts cytotoxicity in several types of cancer cells including gastric cancer cells. However, the mechanism of erastin in regulating metabolic pathways in gastric cancer remains largely unclear. To investigate the gastric cellular response to erastin therapy, a pseudotargeted metabolomics method was achieved on ultra-high performance liquid chromatography-hybrid triple quadrupole linear ion trap mass spectrometry (UHPLC-QTRAP MS), which was used to investigate metabolic changes between erastin-treated MGC-803 cells and the controls at different time points. We found that erastin induced tremendous impact on the metabolome of gastric cells by affecting key metabolic processes, such as cysteine and methionine metabolism, tryptophan metabolism, purine metabolism, glutathione biosynthesis, glycolysis and TCA cycle. Interestingly, S-adenosylmethionine, methionine, serine and cysteine were obviously increasing treads after erastin treatment, while S-adenosylhomocysteine and glutathione were always down-regulated up to 24 h. The results indicated that DNA methylation was activated and glutathione biosynthesis was blocked in erastin-treated MGC-803 gastric cells, highlighting the importance of erastin as a promising drug candidate for in vivo treatment of gastric tumor.

Traceability Research on Dendrobium devonianum Based on SWATHtoMRM.

SWATHtoMRM technology was used in this experiment to further identify and trace the sources of Dendrobium devonianum and Dendrobium officinale produced in the same area using TOF and MS-MRM. After the conversion of the R package of SWATHtoMRM, 191 MRM pairs of positive ions and 96 pairs of negative ions were obtained. Dendrobium devonianum and Dendrobium officinale can be separated very well using the PCA and PLS-DA analysis of MRM ion pairs; this shows that there are obvious differences in chemical composition between Dendrobium devonianum and Dendrobium officinale, which clearly proves that the pseudotargeted metabolomics method based on SWATHtoMRM can be used for traceability identification research. A total of 146 characteristic compounds were obtained, with 20 characteristic compounds in Dendrobium devonianum. The enrichment pathways of the characteristic compounds were mainly concentrated in lipids and atherosclerosis, chagas disease, fluid shear stress and atherosclerosis, proteoglycans in cancer, the IL-17 signaling pathway, the sphingolipid signaling pathway, diabetic cardiomyopathy, arginine and proline metabolism, etc., among which the lipid and atherosclerosis pathways were more enriched, and 11 characteristic compounds affected the expression levels of IL-1, TNFα, CD36, IL-1β, etc. These can be used as a reference for research on variety improvement and active substance accumulation in Dendrobium devonianum and Dendrobium officinale.

Pseudotargeted metabolomics-based random forest model for tracking plant species from herbal products

BackgroundThe “one-to-multiple” phenomenon is prevalent in medicinal herbs. Accurate species identification is critical to ensure the safety and efficacy of herbal products but is extremely challenging due to their complex matrices and diverse compositions. PurposeThis study aimed to identify the determinable chemicalome of herbs and develop a reasonable strategy to track their relevant species from herbal products. MethodsTake Astragali Radix-the typical “one to multiple” herb, as a case. An in-house database-driven identification of the potentially bioactive chemicalome (saponins and flavonoids) in AR was performed. Furthermore, a pseudotargeted metabolomics method was first developed and validated to obtain high-quality semi-quantitative data. Then based on the data matrix, the random forest algorithm was trained to predict Astragali Radix species from commercial products. ResultsThe pseudotargeted metabolomics method was first developed and validated to obtain high-quality semi-quantitative data (including 56 saponins and 49 flavonoids) from 26 batches of AR. Then the random forest algorithm was well-trained by importing the valid data matrix and showed high performance in predicting Astragalus species from ten commercial products. ConclusionThis strategy could learn species-special combination features for accurate herbal species tracing and could be expected to promote the traceability of herbal materials in herbal products, contributing to manufacturing standardization.

Comprehensive quality evaluation of Aconiti Lateralis Radix Praeparata based on pseudotargeted metabolomics and simultaneous determination of fifteen components, and development of new processed products of black slices with less toxicity

Aconiti Lateralis Radix Praeparata is one of the most famous traditional Chinese medicines possessing a variety of pharmacological activities on top of the toxicities. Due to the heterogeneity and non-standardization of the processing procedures, the subtypes and contents of the differential compounds between different processed products still remained indistinct, causing great risk in their proper use. In order to achieve the comparison and quality evaluation of different processed products of Aconiti Lateralis Radix Praeparata and develop new processed products with less toxicity, a quantification and pseudotargeted metabolomics method was developed based on the dynamic MRM mode of triple quadrupole (QqQ) mass spectrometry, and multivariate statistical analysis methods were applied to compare different processed products. Method validation results indicated good specificity, linearity, repeatability, precision, stability and recovery of the established quantification method and good linearity, precision and stability of the pseudotargeted metabolomics method. Differential compounds of different processed products were screened out and further confirmed by the quantification results. At last, the processing procedures were optimized to obtain new processed products of “Heishunpian” (black slices) with less toxicity, in which the contents of the toxic diester-type diterpenoid alkaloids were reduced from 106.98 μg/g to 0.85–12.96 μg/g. This study provided a valuable reference for the establishment of comprehensive quality evaluation methods of herbal medicines and a scientific basis for the optimization of processing procedures of Aconiti Lateralis Radix Praeparata.

Pseudotargeted metabolomics revealed the adaptive mechanism of Draba oreades Schrenk at high altitude.

Strong ultraviolet radiation and low temperature environment on Gangshika Mountain, located in the eastern part of the Qilian Mountains in Qinghai Province, can force plants to produce some special secondary metabolites for resisting severe environmental stress. However, the adaptive mechanism of Draba oreades Schrenk at high altitude are still unclear. In the current study, Draba oreades Schrenk from the Gangshika Mountain at altitudes of 3800 m, 4000 m and 4200 m were collected for comprehensive metabolic evaluation using pseudotargeted metabolomics method. Through KEGG pathway enrichment analysis, we found that phenylpropanoid biosynthesis, phenylalanine, tyrosine and tryptophan biosynthesis and phenylalanine metabolism related to the biosynthesis of flavonoids were up-regulated in the high-altitude group, which may enhance the environmental adaptability to strong ultraviolet intensity and low temperature stress in high altitude areas. By TopFc20 distribution diagram, the content of flavonoids gradually increased with the elevation of altitude, mainly including apigenin, luteolin, quercetin, hesperidin, kaempferol and their derivatives. Based on the random forest model, 10 important metabolites were identified as potential biomarkers. L-phenylalanine, L-histidine, naringenin-7-O-Rutinoside-4'-O-glucoside and apigenin related to the flavonoids biosynthesis and plant disease resistance were increased with the elevation of altitude. This study provided important insights for the adaptive mechanism of Draba oreades Schrenk at high altitude by pseudotargeted metabolomics.

Plasma metabolic signatures for intracranial aneurysm and its rupture identified by pseudotargeted metabolomics

Background and aimsThe vital metabolic signatures for IA risk stratification and its potential biological underpinnings remain elusive. Our study aimed to develop an early diagnosis model and rupture classification model by analyzing plasma metabolic profiles of IA patients. Materials and methodsPlasma samples from a cohort of 105 participants, including 75 IA patients in unruptured and ruptured status (UIA, RIA) and 30 control participants were collected for comprehensive metabolic evaluation using ultra-high-performance liquid chromatography–mass spectrometry-based pseudotargeted metabolomics method. Furthermore, an integrated machine learning strategy based on LASSO, random forest and logistic regression were used for feature selection and model construction. ResultsThe metabolic profiling disturbed significantly in UIA and RIA patients. Notably, adenosine content was significantly downregulated in UIA, and various glycine-conjugated secondary bile acids were decreased in RIA patients. Enriched KEGG pathways included glutathione metabolism and bile acid metabolism. Two sets of biomarker panels were defined to discriminate IA and its rupture with the area under receiver operating characteristic curve of 0.843 and 0.929 on the validation sets, respectively. ConclusionsThe present study could contribute to a better understanding of IA etiopathogenesis and facilitate discovery of new therapeutic targets. The metabolite panels may serve as potential non-invasive diagnostic and risk stratification tool for IA.

Biomarkers of Metabolomics in Inflammatory Bowel Disease and Damp-Heat Syndrome: A Preliminary Study.

Aims This study aims to investigate the potential biomarkers of inflammatory bowel disease (IBD) and IBD with damp-heat syndrome (IBD-DH) by metabolomics. Methods Plasma and urine samples were collected from 15 healthy controls and 30 IBD patients, including 15 IBD-DH and 15 IBD with spleen deficiency syndrome (IBD-SD), which was coded as SF8G and SF70 according to the International Classification of Diseases Eleventh Revision (ICD-11) issued by World Health Organization. Pseudotargeted metabolomics method was used based on ultra-high-performance liquid chromatography-high-resolution mass spectrometry and triple-quadrupole mass spectrometry. Results Under the condition of false discovery rate (FDR) < 0.05, variable importance projection (VIP) > 1.0, and fold change (FC) > 1.5 or < 2/3, we found 57 plasma differential metabolites and 20 urinary differential metabolites in IBD. Then, with area under the curve (AUC) ≥ 0.85 and FC ≥ 2 or ≤ 0.3, 11 potential biomarkers were identified, such as acylcarnitine (ACar 20:4, ACar 18:1, and ACar 20:3), 3-indoleacetic acid, hippuric acid, and dehydroepiandrosterone sulfate, which is related to intestinal microbiota and immune response. However, less obvious differences were observed in IBD-DH when compared with IBD-SD. Under the condition of FDR < 0.2, VIP >1.0, and FC > 1.5 or < 2/3, we identified 16 plasma differential metabolites. In urine samples, IBD-DH and IBD-SD had the same metabolite pattern. With AUC ≥ 0.80, 7 differential plasma metabolites, mainly glycerophospholipids, were identified in IBD-DH. Kyoto Encyclopedia of Genes and Genomes analysis indicated that metabolic pathways, such as citrate cycle and amino acids metabolism, were mainly responsible for the distinction between IBD and healthy controls, whereas glycerophospholipid metabolism perturbation was not only a manifestation of IBD but also an important pathway to distinguish two subtypes defined by traditional medicine, IBD-DH and IBD-SD. Conclusion In this study, we found that several metabolites of aromatic acids and lipid derivatives could act as potential biomarkers to discriminate IBD from healthy controls. Glycerophospholipids metabolites might be used to differentiate IBD-DH from IBD-SD.

Comprehensive pseudotargeted metabolomics analysis based on two-phase liquid extraction-UHPLC-MS/MS for the investigation of depressive rats.

Pseudotargeted analysis combines the advantages of untargeted and targeted metabolomics methods. This study proposed a comprehensive pseudotargeted metabolomics method based on two-phase liquid extraction using ultra-high-performance liquid chromatography-tandem mass spectrometry. Two-phase liquid extraction, composed of both aqueous and organic phases, extracted a wide range of metabolites from polar to nonpolar in plasma samples. Besides, the two phases were combined and detected in a single injection to save analytical time. A total of 486 potential metabolites were detected by the developed approach. Compared with the conventional methanol-based protein precipitation method, the two-phase liquid extraction method significantly increased the metabolite coverage by 20.29%. Besides, the proposed pseudotargeted metabolomics method exhibited higher sensitivity and better repeatability than the untargeted method. Finally, we applied the established pseudotargeted method to the metabolomics study of depressive rats and screened 53 differential variables. Sixteen determined differential metabolites were mainly in four metabolic pathways including glycerophospholipid, arachidonic acid, sphingolipid metabolisms, pentose and glucuronate interconversions. The results indicated that the pseudotargeted method based on two-phase liquid extraction broadened the metabolite coverage with good sensitivity and repeatability, exhibiting significant potential for discovering differential metabolites in metabolomics studies.

Identification of Veratrum Species in Pimacao Based on ITS2 Sequences and Steroidal Alkaloids by a Pseudo-Targeted Metabolomics Method.

Pimacao is a traditional Chinese folk medicine and is the main component of the famous Chinese herbal remedy “Yunnan Baiyao” for its significant analgesic activity in the treatment of wounds. Due to increases in consumption, its wild population is now difficult to find, and adulterant from the same genus has occurred. However, this is challenging to distinguish the species of Veratrum in Pimacao using dried roots and rhizomes or medicinal powder. ITS2 sequences and steroidal alkaloids by the non-targeted and pseudo-targeted metabolomics methods were taken advantage of establishing an effective identification method. Based on the ITS2 sequence, metabolite profiling of steroidal alkaloids and morphological characteristics, the classification of two distinct subspecies in V. mengzeanum has been reinforced. In addition, the new subspecies V. mengzeanum subsp. phuwae was collected in China for the first time. The ITS2 sequence could be used in the identification of V. taliense, V. mengtzeanum, V. stenophyllum, and V. nigrum, but is insufficient for intraspecific identification. Simultaneously, 147 variables were labeled by non-targeted analysis accomplished utilizing an ultra-high-performance liquid chromatography electrospray ionization orbitrap tandem mass spectrometry (UPLC-ESI-QE-Orbitrap-MS) system consisting of an Orbitrap QE HF-X. Followed by a pseudo-targeted analysis method developed for the Qtrap 6500-plus mass spectrometry system coupled with an ESI source, 29 labeled steroidal alkaloids detected by the MRM mode could distinguish between four species. Notably, 25 labeled steroidal alkaloids could distinguish between three closely related species. These have the potential to be used as markers for identification. Furthermore, there were several variables with statistical differences between two subspecies of V. mengtzeanum and populations of V. taliense, V. mengtzeanum, and V. stenophyllum.

Pseudotargeted Metabolomic Fingerprinting and Deep Learning for Identification and Visualization of Common Pathogens.

Matrix-assisted laser desorption/ionization time-of-flight mass (MALDI-TOF) spectrometry fingerprinting has reduced turnaround times, costs, and labor as conventional procedures in various laboratories. However, some species strains with high genetic correlation have not been directly distinguished using conventional standard procedures. Metabolomes can identify these strains by amplifying the minor differences because they are directly related to the phenotype. The pseudotargeted metabolomics method has the advantages of both non-targeted and targeted metabolomics. It can provide a new semi-quantitative fingerprinting with high coverage. We combined this pseudotargeted metabolomic fingerprinting with deep learning technology for the identification and visualization of the pathogen. A variational autoencoder framework was performed to identify and classify pathogenic bacteria and achieve their visualization, with prediction accuracy exceeding 99%. Therefore, this technology will be a powerful tool for rapidly and accurately identifying pathogens.

Development of a plasma pseudotargeted metabolomics method based on ultra-high-performance liquid chromatography-mass spectrometry.

Untargeted methods are typically used in the detection and discovery of small organic compounds in metabolomics research, and ultra-high-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) is one of the most commonly used platforms for untargeted metabolomics. Although they are non-biased and have high coverage, untargeted approaches suffer from unsatisfying repeatability and a requirement for complex data processing. Targeted metabolomics based on triple-quadrupole mass spectrometry (TQMS) could be a complementary tool because of its high sensitivity, high specificity and excellent quantification ability. However, it is usually applicable to known compounds: compounds whose identities are known and/or are expected to be present in the analyzed samples. Pseudotargeted metabolomics merges the advantages of untargeted and targeted metabolomics and can act as an alternative to the untargeted method. Here, we describe a detailed protocol of pseudotargeted metabolomics using UHPLC-TQMS. An in-depth, untargeted metabolomics experiment involving multiple UHPLC-HRMS runs with MS at different collision energies (both positive and negative) is performed using a mixture obtained using small amounts of the analyzed samples. XCMS, CAMERA and Multiple Reaction Monitoring (MRM)-Ion Pair Finder are used to find and annotate peaks and choose transitions that will be used to analyze the real samples. A set of internal standards is used to correct for variations in retention time. High coverage and high-performance quantitative analysis can be realized. The entire protocol takes ~5 d to complete and enables the simultaneously semiquantitative analysis of 800-1,300 metabolites.

Pseudotargeted Method Based on Parallel Column Two-Dimensional Liquid Chromatography-Mass Spectrometry for Broad Coverage of Metabolome and Lipidome.

Metabolite and lipid profilings usually need two liquid chromatography-mass spectrometry (LC-MS) methods because of a great polarity difference. A pseudotargeted metabolomics method as a novel emerging approach can integrate the advantages of nontargeted and targeted methods. Here, we aim to establish a comprehensive method for metabolome and lipidome by using a parallel column-based two-dimensional LC (PC-2DLC)-MS and pseudotargeted approach. To simultaneously extract as many polar metabolites and nonpolar lipids as possible, we systematically optimized the sample pretreatment process, and isopropanol/methanol (3:1, v/v) and isopropanol/water (7:3, v/v) were selected as the extraction and reconstitution solvents, respectively. The detected triglycerides significantly increased after the sample pretreatment optimization. Then PC-2DLC coupled with Triple TOF MS was applied to analyze a mixed sample from serum, urine, and liver tissue matrixes. The multiple reaction monitoring (MRM) transitions of the metabolome and lipidome were defined according to the "MRM-Ion Pair Finder" software and lipidomics MRM-transition database, respectively. After verification by QTRAP MS in the scheduled MRM mode, 1609 potential metabolites and lipids corresponding to 1294 MRM transitions, and 847 potential metabolites and lipids corresponding to 687 MRM transitions were detected in positive and negative ion modes, respectively. They range at about 30 orders of magnitude in octanol/water partition coefficient. The pseudotargeted 2DLC-MS method was validated to have good analytical characteristics. As a proof of applicability, sera from type 2 diabetic patients were investigated by the established method. The results indicated that the pseudotargeted 2DLC-MS method is reliable and repeatable and can be used in a metabolomics study.

Analysis of fatty acids in rice by pseudotargeted metabolomics method based on gas chromatography-mass spectrometry

A pseudotargeted metabolomics method based on gas chromatography-mass spectrometry (GC-MS) was developed for the analysis of fatty acids in rice. A total of 16 fatty acids were detected in rice. The method was used to identify the difference between fatty acid profiles in rice. The total intensity of the saturated and unsaturated fatty acids was used as the evaluation index. The effects of six extraction methods and four extraction solvents on the extraction efficiencies of the fatty acids were compared. The developed method was used to investigate the fatty acid profiles in five types of rice (Daohuaxiang, Jixing, Jinlangzi, Nongda, and Zhuangyuan). The fatty acid profile in Daohuaxiang rice was different from that in the other four species. The fatty acids in Jinlangzi and Nongda rice were markedly different, while those in Jixing and Jinlangzi rice were similar. The method is simple, stable and accurate, and it can provide basic data for the improvement of rice quality and nutritional value.

The application of pseudotargeted metabolomics method for fruit juices discrimination

To optimize and evaluate the pseudotargeted metabolomics for juice discrimination and authentication, five widely consumed fruit (apple, orange, pear, purple grape and mandarin) juices were selected. SWATH-MS data was acquired by various windows being calculated based on total ion current, and then 2310 and 2292 MRM transitions were generated. Most of them (1522 and 1872) were detected in positive and negative modes. Distinctive separation among these juices could be observed from principal component analysis and hierarchical clustering analysis. After analysis of variance, fold change analysis and orthogonal projection to latent structures discriminant analysis, 57 potential markers were defined. Subsequently, 33 markers were putatively annotated, which could be used for juice discrimination and authentication. And 7 markers including l-phenylalanine, ascorbic acid, adenosine, epicatechin, glutathione, chlorogenic acid and nobiletin, were confirmed by standards. It is clearly indicated that pseudotargeted metabolomics could make great contribution to food industry as a new emerging technique.

Development of a mass spectrometry-based pseudotargeted metabolomics strategy to analyze hormone-stimulated gastric cancer cells

Gastric cancer (GC) is the third most common cause of cancer death worldwide, and the incidence of GC is higher in males than females. To investigate the gastric cellular response to hormone therapy, we developed a cell pseudotargeted metabolomics method based on liquid chromatography-hybrid triple quadrupole linear ion trap mass spectrometry (LC-QTRAP MS). Chromatographic separation, sample analysis and metabolite extraction were optimized in an integrated manner. The established pseudotargeted method, which combined nontargeted and targeted analyses, exhibited high selectivity, good repeatability and wide metabolome coverage. The method was then applied to discover differential metabolites from hormone-stimulated gastric cancer cells compared with the controls for the first time. The results demonstrated that hormone had subtle but phenotypically important alterations in nucleotide metabolism, amino acid metabolism, glycolysis, tricarboxylic acid (TCA) cycle, aminoacyl-tRNA biosynthesis and so on, which indicate that the developed method is a powerful tool for effective screening of endogenous polar metabolites in cell samples.

Development of a metabolic pathway-based pseudo-targeted metabolomics method using liquid chromatography coupled with mass spectrometry

The pseudo-targeted metabolomics approach was developed recently which combined the advantages of untargeted and targeted analysis. However, the current pseudo-targeted analysis method has limitations due to the technical characteristics. In this study, a novel metabolic pathway-based pseudo-targeted approach was proposed for urine metabolomics analysis using an ultra-high-performance liquid chromatography (UPLC)-MS/MS system operated in the multiple reaction monitoring (MRM) mode. MRM ion pairs were acquired from urine samples through untargeted analysis using UPLC-HRMS, as well as by searching for metabolites in related pathways in relevant databases and from previous relevant research, including amino acids, fatty acids, nucleosides, carnitines, glycolysis metabolites, and steroids. This improved pseudo-targeted method exhibited good repeatability and precision, and no complicated peak alignment was required. As a proof of concept, the developed novel method was applied to the discovery of urine biomarkers for patients with esophageal squamous cell carcinoma (ESCC). The results showed that ESCC patients had altered acylcarnitines, amino acids, nucleosides, and steroid derivative levels et al. compared to those of healthy controls. The novelty of this study lies in the fact that it provides an approach for acquiring MRM ion pairs not only from untargeted MS analysis but also from targeted searching for metabolites in related metabolic pathways. By improving the detection limit of low-abundance metabolites, it enlarges the range for the discovery of potential biomarkers. Our work provides a foundation for achieving pseudo-targeted metabolomics analysis on the widely used LC-MS/MS MRM platform.

Ion-Pair Selection Method for Pseudotargeted Metabolomics Based on SWATH MS Acquisition and Its Application in Differential Metabolite Discovery of Type 2 Diabetes.

The pseudotargeted metabolomics method integrates advantages of nontargeted and targeted analysis because it can acquire data of metabolites in the multireaction monitoring (MRM) mode of mass spectrometry (MS) without needing standards. The key is the ion-pair information collection from samples to be analyzed. It is well-known that sequential windowed acquisition of all theoretical Fragment ion (SWATH) MS mode can acquire MS2 information to a maximum extent. To expediently acquire as many ion-pairs as possible with optimal collision energy (CE), an ion-pair selection approach based on SWATH MS acquisition with variable isolation windows was developed in this study. Initially, nontargeted acquisition of all metabolites information in plasma Standard Reference Material (SRM 1950) was performed by ultra high-performance liquid chromatography (UHPLC)-quadrupole time-of-flight (Q-TOF) MS platform with three CEs. With the help of software tool, the ion-pairs of unique metabolites were gained. Then they were validated in scheduled MRM coupled with UHPLC. After removing false positive, the ion-pairs with an optimal CE was integrated. A total of 1373 unique metabolite ion-pairs were obtained at positive ion mode. And repeatability of the established pseudotargeted approach was evaluated by intraday and interday precision. The results demonstrated the method was stable, reliable, and suitable for metabolomics study. As an application example, alterations of serum metabolites in Type 2 diabetes were investigated by using the established method. This work provides a pseudotargeted ion-pair selection method based on SWATH MS acquisition with the characters of increased metabolite coverage, suitable CE, and convenient processing.

An improved pseudotargeted metabolomics approach using multiple ion monitoring with time-staggered ion lists based on ultra-high performance liquid chromatography/quadrupole time-of-flight mass spectrometry

Pseudotargeted metabolomics is a novel strategy integrating the advantages of both untargeted and targeted methods. The conventional pseudotargeted metabolomics required two MS instruments, i.e., ultra-high performance liquid chromatography/quadrupole-time- of-flight mass spectrometry (UHPLC/Q-TOF MS) and UHPLC/triple quadrupole mass spectrometry (UHPLC/QQQ-MS), which makes method transformation inevitable. Furthermore, the picking of ion pairs from thousands of candidates and the swapping of the data between two instruments are the most labor-intensive steps, which greatly limit its application in metabolomic analysis. In the present study, we proposed an improved pseudotargeted metabolomics method that could be achieved on an UHPLC/Q-TOF/MS instrument operated in the multiple ion monitoring (MIM) mode with time-staggered ion lists (tsMIM). Full scan-based untargeted analysis was applied to extract the target ions. After peak alignment and ion fusion, a stepwise ion picking procedure was used to generate the ion lists for subsequent single MIM and tsMIM. The UHPLC/Q-TOF tsMIM MS-based pseudotargeted approach exhibited better repeatability and a wider linear range than the UHPLC/Q-TOF MS-based untargeted metabolomics method. Compared to the single MIM mode, the tsMIM significantly increased the coverage of the metabolites detected. The newly developed method was successfully applied to discover plasma biomarkers for alcohol-induced liver injury in mice, which indicated its practicability and great potential in future metabolomics studies.