Electrospray Ionization Ion Mobility Mass Spectrometry.

Electrospray ionization ion mobility mass spectrometry (ESI-IMS-MS) is a rapidly progressing analytical technique for the examination of complex compounds in the gas phase. ESI-IMS-MS separates isomers, provides structural information, and quantitatively identifies peptides, lipids, carbohydrates, polymers, and metabolites in biological samples. ESI-IMS-MS has pharmaceutical, environmental, and manufacturing applications quickly characterizing drugs, petroleum products, and metal macromolecules. This review provides the history of ESI-IMS-MS development and applications to date.

Development of a Metabolite Ratio Rule-Based Method for Automated Metabolite Profiling and Species Differentiation of Four Major Cinnamon Species.

A metabolomic ratio rule-based classification method was developed and programmed for automated metabolite profiling and differentiation of four major cinnamon species using ultra-high-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS). The computational program identifies key cinnamon metabolites, including proanthocyanidins, cinnamaldehyde, and coumarin, from test samples through LC-MS data processing and assigns cinnamon species by critical metabolite ratios using a stepwise classification strategy. Further, 100% classification accuracy was achieved on the training sample set through critical ratio optimization, and over 95% accuracy was achieved on the validation sample set. The proposed cinnamon classification method exhibited superior accuracy compared to the metabolomic-based PLS-DA modeling method and offered great value for the authentication of cinnamon samples and evaluation of their potential health benefits.

Study on Human Urinary Metabolic Profiles after Consumption of Kale and Daikon Radish using a High-resolution Mass Spectrometry-Based Non-targeted and Targeted Metabolomic Approach.

In the present study, urine samples were collected from healthy human volunteers to determine the metabolic fates of phenolic compounds and glucosinolates after a single meal of kale and daikon radish. The major glucosinolates and phenolic compounds in kale and daikon radish were measured. The urinary metabolome after feeding at different time periods was investigated. A targeted metabolite analysis method was developed based on the known metabolic pathways for glucosinolates and phenolic compounds. Using a targeted approach, a total of 18 metabolites were found in urine: 4 from phenolic compounds and 14 from glucosinolates. Among these metabolites, 4-methylsulfinyl-3-butenyl isothiocyanate, 4-methylsulfinyl-3-butenyl isothiocyanate-cysteine, and 4-methylsulfinyl-3-butenylglucosinolate-N-acetyl cysteine were reported for the first time in human urine. The combination of non-targeted and targeted metabolomic approaches can gain a full metabolite profile for human dietary intervention studies.

Metabolomic profiling and comparison of major cinnamon species using UHPLC-HRMS.

The metabolomic profiles of four major species of cinnamon (Cinnamomum verum, C. burmannii, C. loureiroi, and C. cassia) were investigated by ultra-high-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS). Thirty-six metabolites were tentatively characterized, belonging to various compound groups such as phenolic glycosides, flavan-3-ols, phenolic acids, terpenes, alkaloids, and aldehydes. Principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) on the HRMS data matrix resulted in a clear separation of the four cinnamon species. Coumarin, cinnamaldehyde, methoxycinnamaldehyde, cinnamoyl-methoxyphenyl acetate, proanthocyanidins, and other components varied among the four species. Such variations were used to develop a step-by-step strategy for differentiating the four cinnamon species based on their levels of pre-selected components. This study suggests a significant variation in the phytochemical compositions of different cinnamon species, which have a direct influence on cinnamon's health benefit potentials. Graphical Abstract.

Analysis of Phenolic Compositions in Cranberry Dietary Supplements using UHPLC-HRMS.

The potential human health benefits of American cranberry (Vaccinium macrocarpon Ait.) leads to the popularity of its dietary supplements in the U.S. market. However, the qualities of the cranberry dietary supplements (CDSs) have never been carefully evaluated. In this study, the phenolic components in ten different CDSs were analyzed using ultra-performance liquid chromatography high-resolution mass spectrometry (UHPLC-HRMS). The study found quercetin and myricetin aglycones in most CDSs, but not in cranberry fruits, despite otherwise similar phenolic profiles between CDS and cranberry fruits in general. One supplement with high levels of B-type proanthocyanidins and non-cranberry flavonol rutin was determined to be adulterated by other botanical extracts. The CDSs only possessed 4% to 11% of the phenolic contents comparing to their claimed fresh cranberry equivalents, emphasizing the urgency of standardized product quality control and labelling for CDS manufacture and marketing.

Quantitative analysis of proanthocyanidins in cocoa using cysteamine-induced thiolysis and reversed-phase UPLC.

The thiolysis of B-type proanthocyanidins in cocoa by cysteamine was evaluated and optimized for its application in cocoa proanthocyanidin quantification. Four thiolysis products consisting of epicatechin, catechin, and their thioethers formed with cysteamine were separated and characterized by reversed-phase UPLC with photo diode array (PDA) detection and high-resolution mass spectrometry (HRMS). A thiolysis time of 20 min under 60 °C temperature was determined as the optimal condition for cocoa proanthocyanidin depolymerization. The optimized thiolysis condition was applied to four cocoa bean samples for proanthocyanidin quantification, using commercially available procyanidin B2 dimer as a reference standard. Satisfactory linearity and quantification and detection limits were achieved for the calibration curves, and proanthocyanidin contents determined by thiolysis were found to be higher than those determined by a published method based on normal-phase HPLC with fluorescence detection. Results in this study suggest promising application potential of cysteamine as an odorless thiolysis agent in routine quantitative analysis of B-type proanthocyanidins. Graphical abstract.

Electrostatic repulsion strategy for high-sensitive and selective determination of dopamine in the presence of uric acid and ascorbic acid.

In this work, poly(sodium 4-styrenesulfonate)-functionalized three-dimensional graphene (PFSG) composites were realized via a facile and green strategy. The nanocomposite was characterized by scanning electron microscopy, ultraviolet and visible spectroscopy, X-ray photoelectron spectroscopy, and electrochemical method. An electroanalytical sensor of dopamine (DA) with high sensitivity and selectivity was fabricated based on PFSG modified glassy carbon electrode (GCE). Under the optimum conditions, the negatively charged PFSG composites exhibit strong electrostatic attraction for DA and electrostatic repulsion to the negatively charged ascorbic acid (AA) and uric acid (UA) molecules. Such electrostatic interaction hindered the enrichment of AA and UA on the surface of PSFG/GCE, which make a higher selectivity for the DA even in the presence of 120-fold AA and UA. Owing to the enhanced electron transfer rate and the stronger surface attraction, the current signal of DA on PFSG/GCE was about 160 times enhanced compared with the bare electrode. There was a good linear relationship between the reduction peak current of DA and concentration across the range of 0.002-2.0 µmol L-1 and 2.0-10.0 µmol L-1 with the limit of 0.8 nmol L-1. Further, the PFSG/GCE was applied to the detection of DA in human serum samples. This biosensor is simple, sensitive, selective and highly stable, which provided a new design strategy and a valuable tool to detect DA in complex samples.

A highly selective and sensitive electrochemical sensor for tryptophan based on the excellent surface adsorption and electrochemical properties of PSS functionalized graphene.

A new green method for the synthesis of poly(sodium 4-styrenesulfonate) functionalized graphene (PSS-graphene) in aqueous solution was realized by using graphene oxide nanosheets (GO) functionalized with PSS and ascorbic acid (AA) as an reducing agent. Various techniques, including Fourier transform infrared spectroscopy, X-ray diffraction, scanning electron microscopy and electrochemistry have been utilized to characterize the as-made nanocomposites. The PSS-graphene was used as a modifier to fabricate an electrochemical sensor of tryptophan (Trp). Due to the difference of the adsorption capacity of PSS-graphene for Trp and Tyr, as well as the different charge states of Trp and the other interfering substances, the sensor showed excellent selectivity for Trp. The synergistic amplification of the stronger enrichment and the enhanced electron transfer rate, the signal of Trp on the PSS-graphene modified electrode was about 100-fold enhanced compared to that of the bare GCE. The peak current of Trp is proportional to its concentration in a wide range from 0.04 to 10.0 µmol L-1 with detection limit of 0.02 µmol L-1. Further, the proposed sensor was applied for the detection of Trp in human serum samples. Favorable results revealed that this work provided a new design strategy and a valuable platform for highly selective and sensitive determination of Trp in complex samples.

Nontargeted Metabolomic Study on Variation of Phenolics in Different Cranberry Cultivars Using UPLC-IM - HRMS.

The metabolomic profiles of American cranberry ( Vaccinium macrocarpon) fruits and their variation among 10 diverse cultivars were investigated by ultraperformance liquid chromatography ion-mobility high-resolution mass spectrometry (UPLC-IM - HRMS). Over 80 metabolites, belonging to various phenolic compound groups, were putatively characterized. An HRMS data matrix consisting of 4778 unique ions across the 10 cultivars was built and analyzed by orthogonal projections to latent structures discriminant analysis (OPLS-DA). The 10 cultivars segregated into 4 clusters on the basis of their metabolomic similarities, which largely reflected their genetic backgrounds. Anthocyanins exhibited the most extensive variations among all the cultivars, reflecting the effects of cranberry breeding selection on fruit color. Flavonols, phenolic acid derivatives, and proanthocyanidins also varied among the different cultivars. The nontargeted metabolomic comparison using multivariate analysis proved to be efficient and robust for determining specific metabolite differences among the cultivars.

An ultrasensitive chemiluminescence immunoassay for fumonisin B1 detection in cereals based on gold-coated magnetic nanoparticles.

BACKGROUND: In the present study, a novel highly sensitive magnetic enzyme chemiluminescence immunoassay (MECLIA) was developed to detect fumonisin B1 (FB1 ) in cereal samples. The gold-coated magnetic nanoparticles (Fe3 O4 @Au, GoldMag) were used as solid phase carrier to develop a competitive CLIA for detecting FB1 , in which FB1 in samples would compete with FB1 -ovalbumin coated on the surface of Fe3 O4 @Au nanoparticles for binding with FB1 antibodies. Successively, horseradish peroxidase labeled goat anti-rabbit IgG (HRP-IgG) was conjugated with FB1 antibodies on the microplate. In substrate solution containing luminol and H2 O2 , HRP-IgG catalyzed luminol oxidation by H2 O2 , generating a high chemiluminescence signal. The FB1 immune GoldMag particles were characterized by Fourier transform infrared spectroscopy, scanning electron microscope and zeta potential analysis, etc. RESULTS: The concentrations and the reaction times of these immunoreagents were optimized to improve the performances of this method. The established method could detect as low as 0.027 ng mL-1 FB1 from 0.05 ng mL-1 to 25 ng mL-1 , demonstrating little cross-reaction (less than 2.4%) with other structurally related compounds. The average intrassay relative SD (RSD) (n = 6) was 3.4% and the average interassay RSD (n = 6) was 5.4%. This method was successfully applied for the determination of FB1 in corn and wheat and gave recoveries of between 98-110% and 91-105%, respectively. CONCLUSION: The results of the present study suggest that the MECLIA approach has potential application for high-throughput fumonisin screening in cereals. © 2018 Society of Chemical Industry.

Effect of preprocessing high-resolution mass spectra on the pattern recognition of Cannabis, hemp, and liquor.

High-resolution mass spectrometry (HRMS) combined with pattern recognition was used to discriminate among twenty-five Cannabis samples, twenty hemp samples, and eight liquor samples. The effects of preprocessing on multivariate data analysis were evaluated for Orbitrap high-resolution mass spectra. Different root transformations were evaluated with respect to the bin width and the average classification rates. In addition, linear binning and proportional binning with various resolving powers were studied with respect to the average classification rates. The proportional binning with the square root transformation gave the best overall performance for chemical profiling or spectral fingerprinting. Six classification methods, fuzzy rule-building expert system (FuRES), linear discriminant analysis (LDA), super partial least squares discriminant analysis (sPLS-DA), support vector machine (SVM), SVM classification tree type gap (SVMTreeG), and SVM classification tree type entropy (SVMTreeH) had similar trends in prediction rate with respect to the resolving power. The optimal proportional mass bin width may depend on the data set, i.e., for the Cannabis samples is resolving power 10-4, for the hemp samples and the liquor samples are resolving power 10-3. Hence, data preprocessing methods such as different transformations, binning strategies, and resolving powers are important factors to be optimized for HRMS direct infusion measurements combined with pattern recognition to be an authentication and characterization tool for various products.

Differentiation of Bovine, Porcine, and Fish Gelatins by Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy (ATR-FTIRS) Coupled with Pattern Recognition.

Bovine, porcine, and fish gelatins have been differentiated based on their spectra collected by attenuated total reflectance FTIR spectroscopy (ATR-FTIRS) coupled with pattern recognition. Three tree-based classification methods, a fuzzy rule-building expert system (FuRES), support vector machine classification trees (SVMTreeG and SVMTreeH), and one reference model, super partial least-squares discriminant analysis (sPLS-DA), were evaluated with and without two preprocessing techniques, namely standard normal variate (SNV) and principal component orthogonal signal correction (PC-OSC). Validation of these methods was obtained with 95% confidence intervals with 10 bootstraps and 4 Latin partitions (10:4). The ATR-FTIR spectra were used with four different ranges: full spectra (4000-650 cm-1), fingerprint region (1731-650 cm-1), specified spectra (4000-800 cm-1), and narrow fingerprint region (1731-800 cm-1). Classification rates for the methods were improved with SNV and PC-OSC when they were used separately or together. The highest classification rates were obtained from the narrow fingerprint region with SNV and PC-OSC at 97.4 ± 1.6% for FuRES, 100 ± 0% for sPLS-DA, and 99.3 ± 0.5% for both SVMTreeG and SVMTreeH. ATR-FTIRS combined with pattern recognition is a potential analytical technique for differentiating the sources of bovine, porcine, and fish gelatins with fast and reliable results.

Comparative Study of NMR Spectral Profiling for the Characterization and Authentication of Cannabis.

For the authentication of botanical materials, it is difficult to obtain representative reference materials because botanicals vary significantly with respect to cultivation conditions. Chemical profiling of plant extracts or spectral fingerprinting can differentiate botanicals and group them by their chemical profiles. NMR spectroscopy yields a powerful and useful method for profiling plant extracts. Both 500 MHz 1H and 1H-1H correlation NMR spectroscopy coupled with pattern recognition were used to discriminate among Cannabis samples. A rapid method of analysis was achieved by extracting directly into the deuterated solvent. Spectral ranges including or excluding the downfield region were compared to evaluate the effect on classification accuracy by projected difference resolution. Six classification methods-fuzzy rule-building expert system, linear discriminant analysis (LDA), super partial least-squares discriminant analysis, support vector machine (SVM), and SVM classification trees (SVMTrees)-all gave better classification performance for proton NMR spectra than for proton-proton correlation NMR spectra for seven Cannabis samples. Among the classification methods for a set of 25 Cannabis samples, the 0.5-7.2 plus 7.4-13.0 ppm ranges gave higher prediction rates of greater than 96% when compared to the reduced range of 0.5-7.2 ppm that excluded the downfield range. The LDA method had the best prediction accuracy of 99.8 ± 0.4%. SVMTree methods provide a robust tool, and classification trees are amenable to interpretation. Hence, NMR spectroscopy combined with chemometrics could be used as a fast screening method for the authentication of Cannabis samples.

New peptide inhibitors modulate the self-assembly of islet amyloid polypeptide residues 11-20 in vitro.

The structural transition and misfolding of human islet amyloid polypeptide may cause a common metabolic disease Type 2 diabetes mellitus. Seventeen peptides have been synthesized, possessing different lengths, compositions, and peptide conformation. In this study, the mechanism of these peptides on inhibiting the formation of hIAPP11-20 amyloid fibrils was investigated using a conventional ThT fluorescence assay and microscale thermophoresis. The results showed that short peptides AT, SA, RF, KS, KT and KN, and cyclic peptides cyclic-KS, cyclic-KT and cyclic-KN displayed considerable inhibitory effect on hIAPP11-20 fibril formation and a strong affinity for hIAPP11-20. The detailed investigation indicated that the phenylalanine residue and some special peptide composition significantly inhibit amyloid formation. The peptide conformation of the designed peptide inhibitors may also play an important role. Microscale thermophoresis quantified the binding affinities between hIAPP11-20 and the peptides; and revealed that high affinity binding more likely leads to inhibiting fibril formation of hIAPP11-20 and vice versa, which is in accordance with the results from the ThT assays. These findings suggest a feasible model of peptide inhibitor design for inhibiting amyloid formation. In addition, microscale thermophoresis was proven as a promising rapid method for preliminarily screening inhibitors of hIAPP11-20.

Prediction of total antioxidant activity of Prunella L. species by automatic partial least square regression applied to 2-way liquid chromatographic UV spectral images.

Four different data representations were evaluated for the determination of the total antioxidant activities of four different Prunella L. species, which are Prunella vulgaris, Prunella grandiflora, Prunella laciniata, and Prunella orientalis Bornm. Three different antioxidant assays, 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABST), 2,2-diphenyl-1-picrylhydrazyl (DPPH), and Folin-Ciocalteu (FC) reagent measured the total antioxidant activity and phenolic content of the four Prunella L. species that were extracted with 12 different solvent systems. The data set of 48 Prunella L. extracts was collected by high-performance liquid chromatography (HPLC) with ultraviolet diode array detection. The prediction of total antioxidant activity of Prunella L. species by super partial least square (sPLS) regression was obtained using four different representations of the data; the entire two-way chromatographic-spectral images, the average UV spectra, the total absorbance chromatogram, the lambda max (λmax) chromatogram. The coefficients of determination (R2) for the entire two-way chromatographic-spectral images (the ABST (0.943±0.008), the DPPH (0.91±0.01), and the FC (0.963±0.006)) indicated good accuracy for predicting antioxidant activities. The three different wet chemical assays are known to yield different values so it is advantageous to estimate the three separate values with a single LC measurement. The entire two-way chromatographic-spectral images have been used to the first time for calibration. Acidic hexane, as an extraction solvent, gave the least root mean square error of prediction (RMSEP) for the two-way chromatographic-spectral images, so it would be the best solvent for modeling antioxidant activities.

DIFFERENTIATION OF AURANTII FRUCTUS IMMATURUS AND FRUCTUS PONICIRI TRIFOLIATAE IMMATURUS BY FLOW-INJECTION WITH ULTRAVIOLET SPECTROSCOPIC DETECTION AND PROTON NUCLEAR MAGNETIC RESONANCE USING PARTIAL LEAST-SQUARES DISCRIMINANT ANALYSIS.

Two simple fingerprinting methods, flow-injection coupled to ultraviolet spectroscopy and proton nuclear magnetic resonance, were used for discriminating between Aurantii fructus immaturus and Fructus poniciri trifoliatae immaturus. Both methods were combined with partial least-squares discriminant analysis. In the flow-injection method, four data representations were evaluated: total ultraviolet absorbance chromatograms, averaged ultraviolet spectra, absorbance at 193, 205, 225, and 283 nm, and absorbance at 225 and 283 nm. Prediction rates of 100% were achieved for all data representations by partial least-squares discriminant analysis using leave-one-sample-out cross-validation. The prediction rate for the proton nuclear magnetic resonance data by partial least-squares discriminant analysis with leave-one-sample-out cross-validation was also 100%. A new validation set of data was collected by flow-injection with ultraviolet spectroscopic detection two weeks later and predicted by partial least-squares discriminant analysis models constructed by the initial data representations with no parameter changes. The classification rates were 95% with the total ultraviolet absorbance chromatograms datasets and 100% with the other three datasets. Flow-injection with ultraviolet detection and proton nuclear magnetic resonance are simple, high throughput, and low-cost methods for discrimination studies.

New insights into side effect of solvents on the aggregation of human islet amyloid polypeptide 11-20.

The formation of highly ordered fibrils for the human islet amyloid polypeptide (hIAPP) is considered as one of the precipitating factors of type 2 diabetes mellitus. In this study, an emerging new approach microscale thermophoresis and conventional ThT fluorescence assay were utilized to investigate the aggregation behavior of hIAPP(11-20), giving a new insight of the solvent effect on the aggregation of hIAPP(11-20). hIAPP(11-20) displayed different aggregation behaviors in various buffers, revealing that hIAPP(11-20) not only self-aggregates but also binds to solvent components. hIAPP(11-20) had a higher binding affinity for Tris than other selected buffers because multiple hydrogen bonds form, resulting in weaker self-aggregation of hIAPP(11-20) at the early stage of aggregation and prolonging the fibril formation process. hIAPP(11-20) displayed similar self-aggregation in both HEPES and pure water. Negatively charged phosphate ions in the PBS solution 'neutralize' the charges carried by hIAPP(11-20) itself to some extent, causing rapid aggregation of hIAPP(11-20), and leading to a shorter fibrillation process of hIAPP(11-20). These results revealed that solvents contribute to the aggregation of hIAPP(11-20) and demonstrated the affect of solvents on the activity of biomolecules. Additionally, as a new technique, microscale thermophoresis offers a powerful and promising approach to study the early stages of aggregation of peptides or proteins.

Application of chemometrics to resolve overlapping mass spectral peak clusters between trichloroethylene and its deuterated internal standard.

RATIONALE: Using one or two (2) H-atom-labeled analogs as internal standards (ISs) may cause a 'cross-contribution' problem (i.e., the overlap of ions from the IS and the analyte) especially for halogenated volatile organic compounds (VOCs). However, in this situation the overlapping peak clusters of the analyte and ISs can be resolved by multivariate chemometric methods such as classical least-squares (CLS) and inverse least-squares (ILS). METHODS: Trichloroethylene (TCE) and its internal standard, deuterated TCE (TCE-d), as model compounds, were analyzed using portable gas chromatography/mass spectrometry. CLS and ILS were applied to resolve overlapping TCE and TCE-d mass spectral signals and evaluated for the determination of TCE. CLS and ILS models were constructed and used to predict concentration ratios of TCE to TCE-d. Calibration samples were prepared by adding TCE at different concentrations and TCE-d at 300 ng mL(-1) as an IS. RESULTS: The calibration curve was linear over a range of 10-1000 ng mL(-1) with a coefficient of determination (R(2)) of 0.993. A validation data set collected 2 weeks later was used to further test the model robustness. Lower prediction errors and higher correlation coefficients were obtained from TCE/TCE-d ratios predicted by the CLS model. CONCLUSIONS: This paper describes the first application of CLS to deconvolute overlapping peaks between an analyte and its corresponding isotopic internal standard for quantification. The proposed method enables simple isotopic analogs of analytes (one H or C atom is isotopically labeled) to be used as internal standards for analytes with isotopic distributions. It has wide application because of the environmental impact and prevalence of halogenated VOCs, especially when analytes have isotopic distributions that overlap with an internal standard or when sophisticated isotopic analogs of the analytes with three or more (2)H- or/and (13)C-atoms are prohibitively expensive or even impossible.

Profiling Amino Acids of Jordanian Scalp Hair as a Tool for Diabetes Mellitus Diagnosis: A Pilot Study.

Hair analysis is an area of increasing interest in the fields of medical and forensic sciences. Human scalp hair has attractive features in clinical studies because hair can be sampled easily and noninvasively from human subjects, and unlike blood and urine samples, it contains a chronological record of medication use. Keratin protein is the major component of scalp hair shaft material and it is composed of 21 amino acids. The method used herein for the amino acid determination in hair included keratin protein acid hydrolysis using 6 M hydrochloric acid (HCl), followed by amino acids derivatization using N,O-bis(trimethylsilyl)trifluoroacetamide (BSTFA), and the determination of derivatized amino acids by gas chromatography/mass spectrometry (GC/MS). Amino acid profiles of scalp hair of 27 Jordanian subjects (15 diabetes mellitus (DM) type 2 patients and 12 control subjects) were analyzed. A fuzzy rule-building expert system (FuRES) classified the amino acid profiles into diabetic and control groups based on multivariate analyses of the abundance of 14 amino acids. The sensitivity and specificity were 100% for diabetes detection using leave-one-individual-out cross-validation. The areas under the receiver operative characteristics (ROC) curves were 1.0, which represents a highly sensitive and specific diabetes test. The nonessential amino acids Gly and Glu, and the essential amino acid Ile were more abundant in the scalp hair of diabetic patients compared to the hair of control subjects. The associations between the abundance of amino acids of human hair and health status may have clinical applications in providing diagnostic indicator or predicting other chronic or acute diseases.

High-selective and sensitive voltammetric sensor for butylated hydroxyanisole based on AuNPs-PVP-graphene nanocomposites.

Gold nanoparticles (AuNPs) and reduced graphene oxide (graphene) composites were synthesized via a simple one-pot approach in the presence of polyvinylpyrrolidone (PVP). Further, the Au-PVP-graphene nanocomposite was used as a new sensing material for the electrochemical detection of butylated hydroxyanisole (BHA). Because of the greatly enlarged surface area, the enhanced electron transfer rate, and a stronger enrichment of BHA, the sensor based on Au-PVP-graphene modified glassy carbon electrode (GCE) displayed highly sensitive electrochemical responses to BHA. Applying linear sweep voltammetry, a good linear relationship of the oxidation peak current with respect to concentrations of BHA across the range of 0.2-100.0 µM and a detection limit of 0.04 µM was achieved. The practical analytical performance of the Au-PVP-graphene/GCE was examined by evaluating detection of BHA in soybean oil and the flour samples. Satisfactory results revealed that this work offered a new way for the sensitive and simple determination of BHA in complex samples.