The metagenomic and metabolomic profile of the gut microbes in Chinese full-term and late preterm infants treated with Clostridium butyricum.

The present study investigated the composition, abundance, and diversity of gut microbes in full-term and late-preterm infants from a medical center in eastern China. A total of 144 genomes of stool samples were captured for 16S rRNA metagenomic analyses. A high abundance of commensal intestinal bacteria was detected in these samples such as Phocaeicola vulgatus, Escherichia coli, and Faecalibacterium prausnitzii, indicating a relatively consistent diversity of gut microbes in the present full-term infants aged 38-40 weeks. However, late preterm infants (n = 50) with mandatory antimicrobials feeding exhibited lower diversity but a higher composition of opportunistic pathogens such as Enterococcus species. Centralized on the situation, we explored the regulatory effect of Clostridium butyricum as probiotics on these late preterm infants. The consumption of C. butyricum did not restore the composition of gut microbes altered by antimicrobials to normal levels, although several opportunistic pathogens decreased significantly after probiotic therapy including Staphylococcus aureus, Sphingomonas echinoides, and Pseudomonas putida. We also compared the effects of day-fed versus night-fed probiotics. Intriguingly, the nighttime feeding showed a higher proportion of C. butyricum compared with probiotic day-feeding. Finally, fecal metabolome and metabolites were analyzed in late preterm infants with (n = 20) or without probiotic therapy (n = 20). The KEGG enrichment analysis demonstrated that vitamin digestion and absorption, synaptic vesicle cycle, and biotin metabolism were significantly increased in the probiotic-treated group, while MSEA indicated that a series of metabolism were significantly enriched in probiotic-treated infants including glycerolipid, biotin, and lysine, indicating the complex effects of probiotic therapy on glutathione metabolism and nutrients digestion and absorption in late preterm infants. Overall, this study provided metagenomic and metabolomic profile of the gut microbes in full-term newborns and late preterm infants in eastern China. Further studies are needed to support and elucidate the role of probiotic feeding in late preterm infants with mandatory antimicrobial treatment.

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. After the MS1 in-source fragment ion identification, both MS1 and MS/MS spectra were constructed for each underlying compound, based on which illegal additives can be precisely identified. The performance of the developed strategy was demonstrated by using mixture and synthetic sample datasets, indicating an improvement of data analysis efficiency up to 70.3 %. Finally, the developed strategy was applied for the screening of unknown additives in 21 batches of commercially available health-care foods. Results indicated that at least 80 % of false-positive results can be reduced and 4 additives were screened and confirmed.

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. The results showed that FDA was superior to PCA and PLS-DA in classifying oak-barrel and stainless steel tanks with oak chips aged wines. As a general conclusion, three-dimensional fluorescence spectroscopy can provide valuable fingerprint information for the identification of oak-barrel and stainless steel tanks with oak chips aged wines, while the study will provide some theoretical references and standards for the quality control and quality assessment of oak-barrel aged 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. Both mixtures of standards and various complex plant matrices were specifically designed for evaluating the performances of the involved method in analyzing both targeted and untargeted metabolomics. Results indicated that AntDAS provide the most acceptable feature extraction, compound identification, and quantification results in targeted compound analysis. Concerning the complex plant dataset, both MS-DIAL and AntDAS can provide more reliable results than the others. The method comparison is maybe useful for the selection of suitable data analysis tools for users.

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). Raw data files were analyzed by our advanced GC-MS data analysis software AntDAS-GCMS. Chemometric methods such as principal component analysis and partial least squares-discrimination analysis have realized the differences of samples with various roasting times. Finally, a total of 51 compounds from 11 aromas were accurately identified and confirmed with standards, and their variations as a function of roasting time were studied. In conclusion, we provided a new solution for the online monitoring of volatile compounds during the industrial roasting process.

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. First, a group of diluted quality control samples was used to screen underlying compounds in samples automatically. Ions in each of the resolved mass spectrum were then evaluated by using the developed algorithms to identify the SIM ion. A Matlab graphical user interface (GUI) was designed to facilitate routine analysis, which can be obtained from http://www.pmdb.org.cn/antdassimopt. The performance of the developed strategy was comprehensively investigated by using standard and complex plant datasets. Results indicated that AntDAS-SIMOpt may be useful for GC-MS-based metabolomics.

Structural elucidation of the impurities in Enzalutamide bulk drug and the development, validation of corresponding HPLC method.

As the first approved androgen receptor(AR) signalling inhibitor, Enzalutamide was approved by the US Food and Drug Administration as an anticancer drug used to treat castration-resistant prostate cancer in 2012. In this manuscript, six potential impurities of Enzalutamide including process impurities and degradation products were studied. The structures of six impurities obtained by synthesis were characterized and confirmed by IR, NMR and MS techniques. In addition, an efficient chromatographic method to separate and quantify these impurities was developed, which achieved on Inertsil ODS-3 column (250mm×4.6mm,5µm) in gradient mode with a mixture of acetonitrile and the ammonium acetate buffer (10mM, pH adjusted to 4.0 with glacial acetic acid). The method was validated with respect to specificity, precision, accuracy, and sensitivity and satisfactory result was achieved. The method was demonstrated to be applicable in routine quality control and stability evaluation of Enzalutamide.

Identification, characterization, and high-performance liquid chromatography quantification of process-related impurities in vonoprazan fumarate.

High-performance liquid chromatography analysis of vonoprazan fumarate, a novel proton pump inhibitor drug revealed six impurities. These were identified by liquid chromatography with mass spectrometry. Further, the structures of the impurities were confirmed by synthesis followed by characterization by mass spectrometry, NMR spectroscopy, and infrared spectroscopy. On the basis of these data and knowledge of the synthetic scheme of vonoprazan fumarate, the previously unknown impurity was identified as 1-[5-(2-fluorophenyl)-1-(pyridin-3-ylsulfonyl)-1H-pyrrol-3-yl]-N-methyldimethylamine, which is a new compound. The possible mechanisms by which these impurities were formed were also discussed. A high-performance liquid chromatography method was optimized in order to separate, selectively detect, and quantify all process-related impurities of vonoprazan fumarate. The presented method has been validated in terms of linearity, limits of detection, and quantification, and response factors and, therefore, is highly suitable for routine analysis of vonoprazan fumarate related substances as well as stability studies.

Stability-indicating reversed-phase HPLC method development and characterization of impurities in vortioxetine utilizing LC-MS, IR and NMR.

The current study reports the development and validation of a stability-indicating reversed phase HPLC method for the separation and identification of potential impurities in vortioxetine, a recently developed antidepressant. The structures of a new compound and four process-related impurities formed during the synthesis were characterized and confirmed by NMR, MS, and IR spectroscopy analyses. The most probable formation mechanisms of the impurities identified were proposed. Based on the characterization data, the new compound was proposed to be 1-[4-[(2,4-dimethylphenyl)thio]phenyl]-piperazine. In addition, an efficient chromatographic method was optimized to separate and quantify the impurities, which were obtained in the 0.05-0.75 µg/mL range. The developed HPLC method was validated with respect to accuracy, precision, linearity, robustness, and limits of detection and quantitation.