AntDAS-GCMS: A New Comprehensive Data Analysis Platform for GC-MS-Based Untargeted Metabolomics with the Advantage of Addressing the Time Shift Problem.

Over the years, a number of state-of-the-art data analysis tools have been developed to provide a comprehensive analysis of data collected from gas chromatography-mass spectrometry (GC-MS). Unfortunately, the time shift problem remains unsolved in these tools. Here, we developed a novel comprehensive data analysis strategy for GC-MS-based untargeted metabolomics (AntDAS-GCMS) to perform total ion chromatogram peak detection, peak resolution, time shift correction, component registration, statistical analysis, and compound identification.

Geographical discrimination of Flos Trollii by GC-MS and UHPLC-HRMS-based untargeted metabolomics combined with chemometrics.

For centuries, Flos Trollii has been consumed as functional tea and a folk medicine in China's north and northwest zones. The quality of Flos Trollii highly depends on the producing zones. Unfortunately, few studies have been reported on the geographical discrimination of Flos Trollii.

Using UHPLC-HRMS-based comprehensive strategy to efficiently and accurately screen and identify illegal additives in health-care foods.

Accurately and high-thoroughly screening illegal additives in health-care foods continues to be a challenging task in routine analysis for the ultrahigh performance liquid chromatography-high resolution mass spectrometry based techniques. In this work, we proposed a new strategy to identify additives in complex food matrices, which consists of both experimental design and advanced chemometric data analysis. At first, reliable features in the analyzed samples were screened based on a simple but efficient sample weighting design, and those related to illegal additives were screened with robust statistical analysis.

Orientin regulates the proliferation and migration of hepatocellular carcinoma cells.

Orientin is a flavone isolated from medicinal plants used in traditional Chinese medicine (TCM) that suppresses the growth of cancer cells in vitro. The effects of orientin in hepatoma carcinoma cells remain unknown. The aim of this paper is to investigate the effects of orientin on the viability, proliferation, and migration of hepatocellular carcinoma cells in vitro.

Identification of Oak-Barrel and Stainless Steel Tanks with Oak Chips Aged Wines in Ningxia Based on Three-Dimensional Fluorescence Spectroscopy Combined with Chemometrics.

With the increased incidence of wine fraud, a fast and reliable method for wine certification has become a necessary prerequisite for the vigorous development of the global wine industry. In this study, a classification strategy based on three-dimensional fluorescence spectroscopy combined with chemometrics was proposed for oak-barrel and stainless steel tanks with oak chips aged wines. Principal component analysis (PCA), partial least squares analysis (PLS-DA), and Fisher discriminant analysis (FDA) were used to distinguish and evaluate the data matrix of the three-dimensional fluorescence spectra of wines.

A comparison of feature extraction capabilities of advanced UHPLC-HRMS data analysis tools in plant metabolomics.

Data analysis of ultrahigh performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS) is an essential and time-consuming step in plant metabolomics and feature extraction is the fundamental step for current tools. Various methods lead to different feature extraction results in practical applications, which may puzzle users for selecting adequate data analysis tools to deal with collected data. In this work, we provide a comprehensive method evaluation for some advanced UHPLC-HRMS data analysis tools in plant metabolomics, including MS-DIAL, XCMS, MZmine, AntDAS, Progenesis QI, and Compound Discoverer.

Carnosol inhibits cerebral ischemia-reperfusion injury by promoting AMPK activation.

Background: Carnosol is a phytopolyphenol (diterpene) found and extracted from plants of Mediterranean diet, which has anti-tumor, anti-inflammatory and antioxidant effects. However, its role in ischemic stroke has not been elucidated.

Methods: Primary neurons subjected to oxygen-glucose deprivation (OGD) was used to investigate the effect of carnosol in vitro.

A study of flavor variations during the flaxseed roasting procedure by developed real-time SPME GC-MS coupled with chemometrics.

Volatile compound variations during the roasting procedure play an essential role in the flaxseed-related product. In this work, we proposed a new strategy to high-throughput characterize the dynamic variations of flavors in flaxseed. Volatile compounds released at various roasting times were comprehensively investigated by a newly developed real-time solid-phase microextraction coupled with gas chromatography-mass spectrometry (GC-MS).

AntDAS-DDA: A New Platform for Data-Dependent Acquisition Mode-Based Untargeted Metabolomic Profiling Analysis with Advantage of Recognizing Insource Fragment Ions to Improve Compound Identification.

Data-dependent acquisition (DDA) mode in ultra-high-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) can provide massive amounts of MS and MS/MS information of compounds in untargeted metabolomics and can thus facilitate compound identification greatly. In this work, we developed a new platform called AntDAS-DDA for the automatic processing of UHPLC-HRMS data sets acquired under the DDA mode. Several algorithms, including extracted ion chromatogram extraction, feature extraction, MS/MS spectrum construction, fragment ion identification, and MS spectrum construction, were developed within the platform.

Chemometric discrimination of the geographical origin of licorice in China by untargeted metabolomics.

Licorice is famous as a herbal medicine and food sweetener. This study provided a comprehensive strategy for investigating the quality of licorice based on untargeted metabolomics. A new strategy for identifying metabolite was developed, including fragment ion identification algorithm and ion fusion algorithm.

A new platform for untargeted UHPLC-HRMS data analysis to address the time-shift problem.

Substantial deviations in retention times among samples pose a great challenge for the accurate screening and identifying of metabolites by ultrahigh-performance liquid chromatography high-resolution mass spectrometry (UHPLC-HRMS). In this study, a coarse-to-refined time-shift correction methodology was proposed to efficiently address this problem. Metabolites producing multiple fragment ions were automatically selected as landmarks to generate pseudo-mass spectra for a coarse time-shift correction.

A chemometric strategy to automatically screen selected ion monitoring ions for gas chromatography-mass spectrometry-based pseudotargeted metabolomics.

The pseudotargeted metabolomics based on gas chromatography-mass spectrometry (GC-MS) has the advantage of filtering out artifacts originating from sample treatment and accurately quantifying underlying compounds in the analyzed samples. However, this technique faces the problem of selecting high-quality selective ions for performing selected ion monitoring (SIM) on instruments. In this work, we proposed AntDAS-SIMOpt, an automatic untargeted strategy for SIM ion optimization that was accomplished on the basis of an experimental design combined with advanced chemometric algorithms.

A chemometric strategy for accurately identifying illegal additive compounds in health foods by using ultra-high-performance liquid chromatography coupled to high resolution mass spectrometry.

The accurate identification of unknown illegal additive compounds in complex health foods continues to be a challenging task in routine analysis, because massive false positive results can be screened with ultra-high-performance liquid chromatography coupled to high-resolution mass spectrometry-based untargeted techniques and must be manually filtered out. To address this problem, we developed a chemometric-based strategy, in which data analysis was first performed by using XCMS, MS-DIAL, Mzmine2, and AntDAS2, to select those that provided acceptable results to extract common features (CFs), which can be detected by all of the selected methods. Then, CFs whose contents were significantly higher in the suspected illegal additive group were screened.

Differentiating Westlake Longjing tea from the first- and second-grade producing regions using ultra high performance liquid chromatography with quadrupole time-of-flight mass spectrometry-based untargeted metabolomics in combination with chemometrics.

There are numerous articles published for geographical discrimination of tea. However, few research works focused on the authentication and traceability of Westlake Longjing green tea from the first- and second-grade producing regions because the tea trees are planted in a limited growing zone with identical cultivate condition. In this work, a comprehensive analytical strategy was proposed by ultrahigh performance liquid chromatography-quadrupole time-of-flight mass spectrometry-based untargeted metabolomics coupled with chemometrics.

A comprehensive automatic data analysis strategy for gas chromatography-mass spectrometry based untargeted metabolomics.

Automatic data analysis for gas chromatography-mass spectrometry (GC-MS) is a challenging task in untargeted metabolomics. In this work, we provide a novel comprehensive data analysis strategy for GC-MS-based untargeted metabolomics (autoGCMSDataAnal) by developing a new automatic strategy for performing TIC peak detection and resolution and proposing a novel time-shift correction and component registration algorithm. autoGCMSDataAnal uses original acquired GC-MS datafiles as input to automatically perform TIC peak detection, component resolution, time-shift correction and component registration, statistical analysis, and compound identification.

A simple method for direct modeling of second-order liquid chromatographic data with retention time shifts and holding the second-order advantage.

Retention time shifts in chromatographic data severely affect the quantitative analysis of analytes of interest in complex systems. This paper offers a simple method for directly handing second-order liquid chromatographic data with retention time shift, and achieving qualitative and quantitative analysis of target analytes in the presence of overlapping peaks and unknown interference, which is the so-called "second-order advantage". The proposed method is named the alternating trilinear decomposition-assisted multivariate curve resolution (ATLD-MCR) because it absorbs the basic philosophy of alternating trilinear decomposition (ATLD) algorithm and multivariate curve resolution (MCR).

Automatic peak detection coupled with multivariate curve resolution-alternating least squares for peak resolution in gas chromatography-mass spectrometry.

Gas chromatography-mass spectrometry (GCMS) has been extensively used in complex sample analysis for the high-throughput characterization of volatile and semivolatile compounds. However, the accurate extraction of compound information remains challenging. Here, we present a combined algorithm strategy for GCMS data analysis to accurately screen metabolites across groups.

Automatic data analysis workflow for ultra-high performance liquid chromatography-high resolution mass spectrometry-based metabolomics.

Data analysis for ultra-performance liquid chromatography high-resolution mass spectrometry-based metabolomics is a challenging task. The present work provides an automatic data analysis workflow (AntDAS2) by developing three novel algorithms, as follows: (i) a density-based ion clustering algorithm is designed for extracted-ion chromatogram extraction from high-resolution mass spectrometry; (ii) a new maximal value-based peak detection method is proposed with the aid of automatic baseline correction and instrumental noise estimation; and (iii) the strategy that clusters high-resolution m/z peaks to simultaneously align multiple components by a modified dynamic programing is designed to efficiently correct time-shift problem across samples. Standard compounds and complex datasets are used to study the performance of AntDAS2.

Automatic untargeted metabolic profiling analysis coupled with Chemometrics for improving metabolite identification quality to enhance geographical origin discrimination capability.

Untargeted metabolic profiling analysis is employed to screen metabolites for specific purposes, such as geographical origin discrimination. However, the data analysis remains a challenging task. In this work, a new automatic untargeted metabolic profiling analysis coupled with a chemometric strategy was developed to improve the metabolite identification results and to enhance the geographical origin discrimination capability.

Tanshinol alleviates impaired bone formation by inhibiting adipogenesis via KLF15/PPARγ2 signaling in GIO rats.

Glucocorticoid (GC)-induced osteoporosis (GIO) is characterized by impaired bone formation, which can be alleviated by tanshinol, an aqueous polyphenol isolated from Salvia miltiorrhiza Bunge. In this study we investigated the molecular mechanisms underlying GC-induced modulation of osteogenesis as well as the possibility of using tanshinol to interfere with GIO. Female SD rats aged 4 months were orally administered distilled water (Con), prednisone (GC, 5 mg·kg·d), GC plus tanshinol (Tan, 16 mg·kg·d) or GC plus resveratrol (Res, 5 mg·kg·d) for 14 weeks.

AntDAS: Automatic Data Analysis Strategy for UPLC-QTOF-Based Nontargeted Metabolic Profiling Analysis.

High-quality data analysis methodology remains a bottleneck for metabolic profiling analysis based on ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry. The present work aims to address this problem by proposing a novel data analysis strategy wherein (1) chromatographic peaks in the UPLC-QTOF data set are automatically extracted by using an advanced multiscale Gaussian smoothing-based peak extraction strategy; (2) a peak annotation stage is used to cluster fragment ions that belong to the same compound. With the aid of high-resolution mass spectrometer, (3) a time-shift correction across the samples is efficiently performed by a new peak alignment method; (4) components are registered by using a newly developed adaptive network searching algorithm; (5) statistical methods, such as analysis of variance and hierarchical cluster analysis, are then used to identify the underlying marker compounds; finally, (6) compound identification is performed by matching the extracted peak information, involving high-precision m/z and retention time, against our compound library containing more than 500 plant metabolites.

Mass-spectra-based peak alignment for automatic nontargeted metabolic profiling analysis for biomarker screening in plant samples.

Nontargeted metabolic profiling analysis is a difficult task in a routine investigation because hundreds of chromatographic peaks are eluted within a short time, and the time shift problem is severe across samples. To address these problems, the present work developed an automatic nontargeted metabolic profiling analysis (anTMPA) method. First, peaks from the total ion chromatogram were extracted using modified multiscale Gaussian smoothing method.