ADAP-GC 3.0: Improved Peak Detection and Deconvolution of Co-eluting Metabolites from GC/TOF-MS Data for Metabolomics Studies

ADAP-GC is an automated computational pipeline for untargeted, GC/MS-based metabolomics studies. It takes raw mass spectrometry data as input and carries out a sequence of data processing steps including construction of extracted ion chromatograms, detection of chromatographic peak features, deconvolution of coeluting compounds, and alignment of compounds across samples. Despite the increased accuracy from the original version to version 2.0 in terms of extracting metabolite information for identification and quantitation, ADAP-GC 2.0 requires appropriate specification of a number of parameters and has difficulty in extracting information on compounds that are in low concentration. To overcome these two limitations, ADAP-GC 3.0 was developed to improve both the robustness and sensitivity of compound detection. In this paper, we report how these goals were achieved and compare ADAP-GC 3.0 against three other software tools including ChromaTOF, AnalyzerPro, and AMDIS that are widely used in the metabolomics community

Distinct Metabolomic Profiles of Papillary Thyroid Carcinoma and Benign Thyroid Adenoma

Papillary thyroid carcinoma (PTC) and benign thyroid adenoma (BTA) are the most common head and neck tumors. However, the metabolic differences between PTC and BTA have not been characterized. The aim of this study was to identify the metabolic profiles of these two types of tumors using a metabolomics approach. Tumors and adjacent nontumor specimens collected from 57 patients with PTC and 48 patients with BTA were profiled using gas chromatography–time-of-flight mass spectrometry and ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry. A panel of 46 and 44 differentially expressed metabolites were identified in the PTC and BTA specimens, respetively, and compared with nontumor tissues. Common metabolic signatures, as characterized by increased glycolysis, amino acid metabolism, one carbon metabolism and tryptophan metabolism, were found in both types of tumors. Purine and pyrimidine metabolism was significantly elevated in the PTC specimens, and taurine and hypotaurine levels were also higher in the PTC tissues. Increased fatty acid and bile acid levels were found, especially in the BTA tissues. The metabolic profiles of the PTC and BTA tissues include both similar and remarkably different metabolites, suggesting the presence of common and unique mechanistic pathways in these types of tumors during tumorigenesis

ADAP-GC 2.0: Deconvolution of Coeluting Metabolites from GC/TOF-MS Data for Metabolomics Studies

ADAP-GC 2.0 has been developed to deconvolute coeluting metabolites that frequently exist in real biological samples of metabolomics studies. Deconvolution is based on a chromatographic model peak approach that combines five metrics of peak qualities for constructing/selecting model peak features. Prior to deconvolution, ADAP-GC 2.0 takes raw mass spectral data as input, extracts ion chromatograms for all the observed masses, and detects chromatographic peak features. After deconvolution, it aligns components across samples and exports the qualitative and quantitative information of all of the observed components. Centered on the deconvolution, the entire data analysis workflow is fully automated. ADAP-GC 2.0 has been tested using three different types of samples. The testing results demonstrate significant improvements of ADAP-GC 2.0, compared to the previous ADAP 1.0, to identify and quantify metabolites from gas chromatography/time-of-flight mass spectrometry (GC/TOF-MS) data in untargeted metabolomics studies

Isotopic Ratio Outlier Analysis of the <i>S. cerevisiae</i> Metabolome Using Accurate Mass Gas Chromatography/Time-of-Flight Mass Spectrometry: A New Method for Discovery

Isotopic ratio outlier analysis (IROA) is a ¹³C metabolomics profiling method that eliminates sample to sample variance, discriminates against noise and artifacts, and improves identification of compounds, previously done with accurate mass liquid chromatography/mass spectrometry (LC/MS). This is the first report using IROA technology in combination with accurate mass gas chromatography/time-of-flight mass spectrometry (GC/TOF-MS), here used to examine the <i>S. cerevisiae</i> metabolome. <i>S. cerevisiae</i> was grown in YNB media, containing randomized 95% ¹³C, or 5%¹³C glucose as the single carbon source, in order that the isotopomer pattern of all metabolites would mirror the labeled glucose. When these IROA experiments are combined, the abundance of the heavy isotopologues in the 5%¹³C extracts, or light isotopologues in the 95%¹³C extracts, follows the binomial distribution, showing mirrored peak pairs for the molecular ion. The mass difference between the ¹²C monoisotopic and the ¹³C monoisotopic equals the number of carbons in the molecules. The IROA-GC/MS protocol developed, using both chemical and electron ionization, extends the information acquired from the isotopic peak patterns for formulas generation. The process that can be formulated as an algorithm, in which the number of carbons, as well as the number of methoximations and silylations are used as search constraints. In electron impact (EI/IROA) spectra, the artifactual peaks are identified and easily removed, which has the potential to generate “clean” EI libraries. The combination of chemical ionization (CI) IROA and EI/IROA affords a metabolite identification procedure that enables the identification of coeluting metabolites, and allowed us to characterize 126 metabolites in the current study

Metabonomic Profiling Reveals Cancer Chemopreventive Effects of American Ginseng on Colon Carcinogenesis in <i>Apc</i>^<i>Min/+</i> Mice

American ginseng (<i>Panax quinquefolius</i> L.) is one of the most commonly used herbal medicines in the West. It has been reported to possess significant antitumor effects that inhibit the process of carcinogenesis. However, the mechanisms underlying its anticancer effects remain largely unresolved. In this study, we investigated the cancer chemopreventive effects of American ginseng on the progression of high fat (HF) diet-enhanced colorectal carcinogenesis with a genetically engineered <i>Apc</i>^<i>Min/+</i> mouse model. The metabolic alterations in sera of experimental mice perturbed by HF diet intervention as well as the American ginseng treatment were measured by gas chromatography time-of-flight mass spectrometry (GC-TOFMS) and liquid chromatography time-of-flight mass spectrometry (LC-TOFMS) analysis. American ginseng treatment significantly extended the life span of the <i>Apc</i>^<i>Min/+</i> mouse. Significant alterations of metabolites involving amino acids, organic acids, fatty acids, and carbohydrates were observed in <i>Apc</i>^<i>Min/+</i> mouse in sera, which were attenuated by American ginseng treatment and concurrent with the histopathological improvement with significantly reduced tumor initiation, progression and gut inflammation. These metabolic changes suggest that the preventive effect of American ginseng is associated with attenuation of impaired amino acid, carbohydrates, and lipid metabolism. It also appears that American ginseng induced significant metabolic alterations independent of the <i>Apc</i>^<i>Min/+</i> induced metabolic changes. The significantly altered metabolites induced by American ginseng intervention include arachidonic acid, linolelaidic acid, glutamate, docosahexaenoate, tryptophan, and fructose, all of which are associated with inflammation and oxidation. This suggests that American ginseng exerts the chemopreventive effects by anti-inflammatory and antioxidant mechanisms

Plasma Metabolite Biomarkers for the Detection of Pancreatic Cancer

Patients with pancreatic cancer (PC) are usually diagnosed at late stages, when the disease is nearly incurable. Sensitive and specific markers are critical for supporting diagnostic and therapeutic strategies. The aim of this study was to use a metabonomics approach to identify potential plasma biomarkers that can be further developed for early detection of PC. In this study, plasma metabolites of newly diagnosed PC patients (<i>n</i> = 100) and age- and gender-matched controls (<i>n</i> = 100) from Connecticut (CT), USA, and the same number of cases and controls from Shanghai (SH), China, were profiled using combined gas and liquid chromatography mass spectrometry. The metabolites consistently expressed in both CT and SH samples were used to identify potential markers, and the diagnostic performance of the candidate markers was tested in two sample sets. A diagnostic model was constructed using a panel of five metabolites including glutamate, choline, 1,5-anhydro-d-glucitol, betaine, and methylguanidine, which robustly distinguished PC patients in CT from controls with high sensitivity (97.7%) and specificity (83.1%) (area under the receiver operating characteristic curve [AUC] = 0.943, 95% confidence interval [CI] = 0.908–0.977). This panel of metabolites was then tested with the SH data set, yielding satisfactory accuracy (AUC = 0.835; 95% CI = 0.777–0.893), with a sensitivity of 77.4% and specificity of 75.8%. This model achieved a sensitivity of 84.8% in the PC patients at stages 0, 1, and 2 in CT and 77.4% in the PC patients at stages 1 and 2 in SH. Plasma metabolic signatures show promise as biomarkers for early detection of PC

Metabolic Transformation of DMBA-Induced Carcinogenesis and Inhibitory Effect of Salvianolic Acid B and Breviscapine Treatment

Oral cancer typically develops from hyperplasia through dysplasia to carcinoma with a multistep process of carcinogenesis involving genetic alterations resulting in aberrant cellular appearance, deregulated cell growth, and carcinoma. The metabolic transformation during the process of oral carcinogenesis and its implications for cancer therapy have not been extensively investigated. Here, we report a metabonomic study on a classical model of 7,12-dimethylbenz(a)anthracene (DMBA)-induced oral carcinogenesis in hamsters to delineate characteristic metabolic transformation during the carcinogenesis using gas chromatography time-of-flight mass spectrometry (GC–TOF MS). Salvianolic acid B (Sal-B), isolated from <i>Salvia miltiorrhiza</i> Bge, and Breviscapine, a flavonoid isolated from Herba Erigerontis, were used to treat the hamsters exposed to DMBA to investigate the molecular mechanism of the inhibitory effect of the two agents on oral carcinogenesis. The dynamic changes of serum metabolic profiles indicated that both Sal-B and Breviscapine were able to attenuate DMBA-induced metabolic perturbation, which is consistent with the histopathological findings that Sal-B and Breviscapine significantly decreased the squamous cell carcinoma (SCC) incidence in the two treatment groups. Significant alterations of key metabolic pathways, including elevated glutaminolysis and glycolysis, and decreased cholesterol and myo-inositol metabolism, were observed in the DMBA-induced model group, which were attenuated or normalized by Sal-B or Breviscapine treatment. Elevated inflammation and tumor angiogenesis at gene and metabolite expression levels were also observed in DMBA-induced oral dysplasia and SCC but were attenuated or normalized by Sal-B and Breviscapine along with significantly decreased incidences of SCC formation

Serum Metabolic Signatures of Fulminant Type 1 Diabetes

Fulminant type 1 diabetes (FT1DM) is a relatively new clinical entity featured by acute destruction of pancreatic beta cells. Clinical consequences of FT1DM could be fatal when timely medications are not provided, suggesting the particular importance of rapid and accurate diagnosis. Here we report a serum metabonomics study of FT1DM patients, together with healthy control subjects (NC), type 2 diabetes (T2DM), classic type 1 diabetes (T1DM), and diabetic ketoacidosis (DKA) patients, with the aim of discovering metabolic markers associated with FT1DM. A total of 79 subjects were enrolled (22 NC, 22 T1DM, 22 T2DM, 8 DKA and 5 FT1DM) and the serum metabolic profiling of fasting blood samples was performed using gas chromatography time-of-flight mass spectrometry (GC-TOFMS) coupled with multivariate and univariate statistical analyses. Serum metabolites differentially expressed in FT1DM relative to NC, or to T2DM, T1DM and DKA were identified. Three metabolite markers, 5-oxoproline, glutamate, and homocysteine, were significantly altered among FT1DM, T2DM, T1DM, and DKA. In addition, the three metabolite markers, 5-oxoproline, glutamate, and homocysteine, presented similar patterns of distribution across groups. The results showed that the metabolic signatures of FT1DM identified in this study could be of potential clinical significance for the accurate diagnosis of FT1DM

Metabonomic Phenotyping Reveals an Embryotoxicity of Deca-Brominated Diphenyl Ether in Mice

Recent studies have demonstrated that polybrominated diphenyl ethers (PBDEs), a group of industrial chemicals, could disrupt thyroid hormone homeostasis and exhibit neurotoxicity, reproductive toxicity, and embryotoxicity. However, clear evidence of embryotoxicity and neurotoxicity of many of these congeners, such as deca-BDE, one of the least bioactive congeners of PBDEs, is still lacking. In the present study, we investigated deca-BDE embryotoxicity by quantitative analysis of two essential thyroid hormones (T4 and T3) and a variety of small-molecule metabolites in the serum of deca-BDE-dosed pregnant mice. Four groups of pregnant C57 mice were administrated with deca-BDE in 20% fat emulsion at a dose of 150, 750, 1 500, or 2 500 mg/kg body weight via gastric intubation on gestation days (g.d.s) 7 to 9, while a control group was given 20% fat emulsion. Maternal mice were euthanized on g.d. 16 and examined for external malformations of the fetus. Maternal serum samples were collected and analyzed by the enzyme linked immunosorbent assay (ELISA) and gas chromatography–time-of-flight mass spectrometry (GC–TOF MS). Using multivariate statistical analysis, we observed a significantly altered metabolic profile associated with deca-BDE embryotoxicity in maternal serum. Our results also demonstrated that deca-BDE at a dose of 2 500 mg/kg body weight induced significant disruption of thyroid hormone metabolism, the TCA cycle, and lipid metabolism in maternal mice, which subsequently led to a significant inhibition of fetal growth and development. We concluded that deca-BDE-induced embryotoxicity closely correlated with global metabolic disruption that can be characterized by thyroid hormone deficiency, disrupted lipid metabolism, and a depleted level of cholesterol in maternal mice

Transcriptomic and Metabonomic Profiling Reveal Synergistic Effects of Quercetin and Resveratrol Supplementation in High Fat Diet Fed Mice

Dietary quercetin and resveratrol have been frequently used in treating various diseases, but the underlying mechanisms are not entirely clear. Here, we report combined transcriptomic and metabonomic profiling that showed that the combined supplementation with quercetin and resveratrol produced synergistic effects on a high-fat diet-induced metabolic phenotype in mice. Histological and phenotypic improvements in serum and hepatic total cholesterol, insulin, fasting blood glucose, and HbA1c were also observed in mice receiving combined quercetin and resveratrol supplementation. This combined quercetin and resveratrol supplementation resulted in significant restoration of gene sets in functional pathways of glucose/lipid metabolism, liver function, cardiovascular system, and inflammation/immunity, which were altered by high fat diet feeding. The integration of transcriptomic and metabonomic data indicated quercetin and resveratrol supplementation enhanced processes of glycolysis and fatty acid oxidation, as well as suppressed gluconeogenesis. These alterations discovered at both the transcriptional and metabolic levels highlight the significance of combined “omics” platforms for elucidating mechanistic pathways altered by dietary polyphenols, such as quercetin and resveratrol, in a synergistic manner