Article
Chemistry, Applied
Hongxia Liu, Yingying Liu, Haolei Han, Chengyin Lu, Hongping Chen, Yunfeng Chai
Summary: This study used ultra-high-performance liquid chromatography/Q-Exactive orbitrap mass spectrometry to identify and characterize phenolamides (PAs) in tea flowers. A total of 21 types of PAs consisting of over 80 isomers were identified, and the majority of them were found in tea flowers for the first time.
Article
Chemistry, Analytical
Chia Yen Liew, Hong-Sheng Luo, Ting-Yi Yang, An-Ti Hung, Bryan John Abel Magoling, Charles Pin-Kuang Lai, Chi-Kung Ni
Summary: This study re-examines high mannose N-glycans in multicellular eukaryotes using a new mass spectrometry method, and identifies many previously unreported isomers. A database is constructed for rapid identification of high mannose N-glycan isomers.
ANALYTICAL CHEMISTRY
(2023)
Article
Biochemistry & Molecular Biology
Eric W. Deutsch, Nuno Bandeira, Yasset Perez-Riverol, Vagisha Sharma, Jeremy J. Carver, Luis Mendoza, Deepti J. Kundu, Shengbo Wang, Chakradhar Bandla, Selvakumar Kamatchinathan, Suresh Hewapathirana, Benjamin S. Pullman, Julie Wertz, Zhi Sun, Shin Kawano, Shujiro Okuda, Yu Watanabe, Brendan MacLean, Michael J. MacCoss, Yunping Zhu, Yasushi Ishihama, Juan Antonio Vizcaino
Summary: This article describes the recent developments in the ProteomeXchange (PX) consortium, which aims to standardize data submission and dissemination of MS proteomics data. The article highlights the increase in the number of datasets submitted to PX resources and the growing data re-use activities.
NUCLEIC ACIDS RESEARCH
(2023)
Article
Chemistry, Applied
Wenlin Wu, Shiyao Liu, Tianrong Guo, Xiying Han, Bing Xia, Yuping Wan, Quanbin Han, Yan Zhou
Summary: A rapid screening method for 70 colorants in dyeable foods was established using UHPLC-Q/Orbitrap MS with customized accurate-mass database and mass spectral library. The method utilized ultrasound-assisted extraction and dispersion solid-phase extraction for sample pretreatment, and evaluated performance in terms of various parameters. The method showed great potential for broad, sensitive, and reliable analysis of colorants in different foods.
Review
Pharmacology & Pharmacy
D. Sala, H. Batebi, K. Ledwitch, P. W. Hildebrand, J. Meiler
Summary: The use of deep machine learning in protein structure prediction allows easy access to annotated conformations, which can compensate for missing experimental structures in structure-based drug discovery. However, the accuracy of these predicted conformations for screening chemical compounds that effectively interact with protein targets is still uncertain. This opinion article examines the benefits and limitations of using state-annotated conformations for ultra-large library screening, particularly for common drug targets like G-protein-coupled receptors.
TRENDS IN PHARMACOLOGICAL SCIENCES
(2023)
Review
Biochemical Research Methods
Yongxin Zhao, Zheng Kuang, Ying Wang, Lei Li, Xiaozeng Yang
Summary: The past two decades have witnessed a surge in studies on microRNAs (miRNAs) in plants and animals. This review article focuses on the progress and challenges of miRNA annotation in plants, comparing it with the annotation of animal miRNAs. Methods and criteria for plant miRNA annotation are discussed along with the potential solutions to existing difficulties, as well as the advantages and disadvantages of bioinformatics tools used in this field. Additionally, the availability of databases hosting plant miRNAs and potential optimization solutions are summarized, with a look towards future challenges and perspectives in plant miRNA annotations.
BRIEFINGS IN BIOINFORMATICS
(2021)
Article
Chemistry, Analytical
Ethan Stancliffe, Michaela Schwaiger-Haber, Miriam Sindelar, Matthew J. Murphy, Mette Soerensen, Gary J. Patti
Summary: The success of precision medicine relies on collecting large-scale data from populations. This study presents an untargeted metabolomics workflow for large-scale projects and uses a reference sample and computational approaches for data processing, resulting in distinct features associated with geographic location.
ANALYTICAL CHEMISTRY
(2022)
Article
Chemistry, Analytical
Ethan Stancliffe, Michaela Schwaiger-Haber, Miriam Sindelar, Matthew J. Murphy, Mette Soerensen, Gary J. Patti
Summary: This paper presents an untargeted metabolomics workflow designed for large-scale projects, which includes evaluating a reference sample and using specific computational methods for data processing and analysis. The study identifies distinct features associated with the geographic location of participants.
ANALYTICAL CHEMISTRY
(2022)
Article
Engineering, Environmental
Kelly L. Pereira, Martyn W. Ward, John L. Wilkinson, Jonathan Brett Sallach, Daniel J. Bryant, William J. Dixon, Jacqueline F. Hamilton, Alastair C. Lewis
Summary: This study presents an automated method for non-targeted compositional analysis of environmental matrices, which has been rigorously tested for reliability and reproducibility using authentic standards. The method detected over 9600 compounds from critical pollutant sources in environmental samples, demonstrating its ability for rapid and comprehensive compound detection.
ENVIRONMENTAL SCIENCE & TECHNOLOGY
(2021)
Article
Chemistry, Analytical
Susy Piovesana, Sara Elsa Aita, Giuseppe Cannazza, Anna Laura Capriotti, Chiara Cavaliere, Andrea Cerrato, Paolo Guarnaccia, Carmela Maria Montone, Aldo Lagana
Summary: Industrial hemp, a valuable plant with various uses, was analyzed for its fatty acid composition using an untargeted approach based on liquid-chromatography and high-resolution mass spectrometry. A total of 39 fatty acid species were tentatively identified, with five fatty acids being the most abundant across all hemp samples. Further targeted quantitative analysis revealed linolenic acid and linoleic acid as the most abundant compounds present.
Article
Chemistry, Analytical
A. Arrizabalaga-Larranaga, S. Epigmenio-Chamu, F. J. Santos, E. Moyano
Summary: This paper describes the development of a rapid and sensitive method for detecting banned dyes in spice samples using UHPLC-MS/MS technology combined with three atmospheric pressure ionization sources. The proposed method demonstrated good performance in sample analysis, with low detection limits, good precision, and accurate quantitation.
ANALYTICA CHIMICA ACTA
(2021)
Review
Oncology
Gang Li, Ping Lin, Ke Wang, Chen-Chen Gu, Souvik Kusari
Summary: This article discusses the importance of natural products from plants and associated microorganisms in the discovery of anticancer drugs, and introduces the application of artificial intelligence techniques in this field.
Article
Chemistry, Applied
Suo Decheng, fan xia, Xiao Zhiming, Wei Shulin, Wang Shi, Wang Peilong
Summary: The method developed enables rapid screening and quantification of progesterone and progestins in milks using UHPLC QE HF HRMS. It meets the validation requirements for veterinary drug residue detection in the EU and China, and has been successfully applied to detect trace levels of progesterone and monitor residual progestins in real milk.
Article
Agricultural Engineering
Qiong Chen, Yushi Zou, Yuqian Zhu, Tianyang Guo, Yiyang Dong, Huanlu Song
Summary: This study used a non-targeted lipidomics analysis platform to determine the lipids in Eucommia ulmoides. The study found that female leaves had a higher abundance of lipids compared to male leaves, and the content of most phospholipids in both genders increased significantly after September. Differences in lipid content between seed cases and leaves were observed, and 53 phospholipids were identified with significantly different contents in the seed cases and fresh leaves samples of Eucommia ulmoides.
INDUSTRIAL CROPS AND PRODUCTS
(2023)
Article
Chemistry, Analytical
Hui-Xia Zhang, Jian-Feng Qin, Jian-Feng Sun, Yu Pan, Tong-Meng Yan, Cai-Yun Wang, Li-Ping Bai, Guo-Yuan Zhu, Zhi-Hong Jiang, Wei Zhang
Summary: Despite the challenges posed by macromolecular nucleic acids, a recent labeling method using N-(tert-butyldimethylsilyl)-N-methyl-trifluoroacetamide (MTBSTFA) has shown promise in the profiling and characterization of DNA and RNA. This method offers advantages such as strong retention, predictable MS2 data, and avoidance of harmful reagents. It has been successfully applied to the analysis of tRNA, including the detection of modified bases and the discovery of new modifications. The ease of access and simplicity of this method make it a valuable tool for researchers.
ANALYTICAL CHEMISTRY
(2023)
Article
Biology
Chao Li, Peng Dou, Tianxiang Wang, Xin Lu, Guowang Xu, Xiaohui Lin
Summary: Studying miRNA synergy and identifying miRNA synergistic modules can help understand complex diseases such as cancers. A new method called DDRM combines knowledge databases and miRNA data to define disease-related modules and construct a weighted miRNA synergistic network. Experiments on TCGA datasets showed that DDRM can accurately distinguish cancer samples from normal samples and outperforms previous methods. Validation on prostate cancer data also demonstrated superior performance. Hence, combining miRNA synergy networks and miRNA data is significant for studying disease mechanisms.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Article
Biochemical Research Methods
Xiaoxiao Wang, Fujian Zheng, Meizhen Sheng, Guowang Xu, Xiaohui Lin
Summary: To improve the accuracy of retention time (RT) prediction, this study proposes a method called multi-data combinations and adaptive neural network (MDC-ANN). MDC-ANN establishes the RT prediction model for a target chromatographic system using transfer learning and a deep learning model trained on a large dataset. Experimental results demonstrate that integrating multiple molecular representations provides more information, improves RT prediction performance, and contributes to compound annotation. Different chromatographic systems may require different molecular representation combinations for accurate RT prediction. Hence, MDC-ANN, which automatically determines the best combination of molecular representations for a specific system, shows promise for accurate RT prediction in real applications.
JOURNAL OF CHROMATOGRAPHY B-ANALYTICAL TECHNOLOGIES IN THE BIOMEDICAL AND LIFE SCIENCES
(2023)
Article
Chemistry, Analytical
Xingyu Guo, Lina Zhou, Yi Wang, Feng Suo, Chuanxia Wang, Wei Zhou, Lingshan Gou, Maosheng Gu, Guowang Xu
Summary: This study developed a LC-MS-based method for neonatal metabolomics analysis of DBS and investigated the influences of blood volume and chromatographic effects on metabolite levels. The method showed good repeatability, precision, and linearity, and was applied to study metabolic disruptions of congenital hypothyroidism.
JOURNAL OF PHARMACEUTICAL AND BIOMEDICAL ANALYSIS
(2023)
Article
Biochemical Research Methods
Xin Lu, Peng Dou, Chao Li, Fujian Zheng, Lina Zhou, Xiaoyu Xie, Zixuan Wang, Guowang Xu
Summary: This study proposes an annotation strategy involving the derivatization of dipeptides and tripeptides via dansylation, which can choose dipeptides/ tripeptides using a small number of standards. A total of 198 dipeptides and 149 tripeptides were annotated, and the variations in serum dipeptides/tripeptides of three different liver diseases were characterized.
JOURNAL OF PROTEOME RESEARCH
(2023)
Article
Neurosciences
Xiaojiao Xu, Qiu Yang, Zheyi Liu, Rong Zhang, Hang Yu, Manli Wang, Sheng Chen, Guowang Xu, Yaping Shao, Weidong Le
Summary: This study aimed to investigate the molecular changes at both metabolic and proteomic levels during the longitudinal progression of ALS and identify the most critical metabolic pathways and underlying mechanisms involved in ALS pathophysiological changes. The study found differential expressions of metabolites involved in purine metabolism, methionine cycle, and glycolysis in ALS mice, and abnormal expressions of enzymes in these metabolic pathways were also confirmed. Additionally, fatty acid metabolism, TCA cycle, arginine and proline metabolism, and folate-mediated one-carbon metabolism were significantly altered in this disease. The identified differential metabolites and proteins could complement existing data on metabolic reprogramming in ALS and provide new insights into the pathological mechanisms and therapeutic targets of ALS.
NEUROBIOLOGY OF DISEASE
(2023)
Review
Chemistry, Analytical
Di Yu, Lina Zhou, Xinyu Liu, Guowang Xu
Summary: The introduction of stable isotope labeling (SIL) technology has become a routine tool for functional metabolomics studies and allows for a deeper understanding of dynamic metabolic regulation in organisms. Mass spectrometry (MS) techniques have shown great vitality in this field by utilizing the different mass spectrometric characteristics between endogenous metabolites and their isotope-labeling forms. Recent advances in MS-based stable isotope-resolved metabolomics (SIRM) methods have expanded the breadth and depth of SIRM research by improving sample pretreatment, MS analysis, and data analysis. This review describes the recent progress of SIRM methods, summarizes their applications in metabolite identification, accurate quantification, and metabolic flux analysis, and discusses current limitations and challenges.
TRAC-TRENDS IN ANALYTICAL CHEMISTRY
(2023)
Article
Biochemistry & Molecular Biology
Xiaoshan Sun, Zhen Jia, Yuqing Zhang, Xinjie Zhao, Chunxia Zhao, Xin Lu, Guowang Xu
Summary: Direct infusion nanoelectrospray high-resolution mass spectrometry (DI-nESI-HRMS) is a promising tool for high-throughput metabolomics analysis. To overcome the limitations of metabolite assignment, a serum metabolome characterization method using a reaction network combined with mass accuracy and isotopic patterns filter was proposed. The approach was validated and compared to database search, showing improved coverage and accuracy rates. The method was then applied to a case study in diabetes metabolomics.
Article
Nanoscience & Nanotechnology
Ruibin Qiang, Haofei Huang, Jia Chen, Xianzhe Shi, Zengjie Fan, Guowang Xu, Hongdeng Qiu
Summary: Rheumatoid arthritis (RA) is characterized by inflammation and pain in the joints, caused in part by a lack of lubrication and excessive proinflammatory proteins. Researchers have developed two potential nanoagents, derived from herbal medicine, that offer both improved joint lubrication and anti-inflammatory effects, showing promise for treating RA.
ACS APPLIED MATERIALS & INTERFACES
(2023)
Article
Chemistry, Analytical
Xiaoshan Sun, Yueyi Xia, Xinjie Zhao, Xinxin Wang, Yuqing Zhang, Zhen Jia, Fujian Zheng, Zaifang Li, Xiuqiong Zhang, Chunxia Zhao, Xin Lu, Guowang Xu
Summary: Direct-infusion Fourier transform ion cyclotron resonance mass spectrometry (DI-FTICR MS) is a promising method for metabolomic analysis with ultrahigh mass accuracy and resolution. In this study, a novel deep characterization approach of serum metabolome was proposed using a segment-optimized spectral-stitching DI-FTICR MS method. This method combines high-confidence and database-independent formula assignments to achieve highly efficient acquisition and accurate assignment of thousands of features in a pooled human serum sample.
ANALYTICAL CHEMISTRY
(2023)
Article
Chemistry, Analytical
Xinxin Wang, Chao Li, Zaifang Li, Yanpeng Qi, Xiuqiong Zhang, Xinjie Zhao, Chunxia Zhao, Xiaohui Lin, Xin Lu, Guowang Xu
Summary: In this study, a structure-guided molecular network strategy (SGMNS) is proposed for deep annotation of untargeted metabolomics data. The strategy utilizes a global connectivity molecular network (GCMN) constructed based on molecular fingerprint similarity of chemical structures in metabolome databases. SGMNS performs network annotation propagation using known metabolites as seeds and achieves high annotation accuracy and precision.
ANALYTICAL CHEMISTRY
(2023)
Article
Environmental Sciences
Yuting Wang, Lina Zhou, Tiantian Chen, Lei You, Xianzhe Shi, Xinyu Liu, Sijia Zheng, Jie Jiang, Yuebin Ke, Guowang Xu
Summary: In this study, a 2D-LC-HRMS-based screening strategy was developed for simultaneously screening pesticides, veterinary/human drugs, and other chemical pollutants in serum. The method was validated to detect 92% and 81% of 1022 residues spiked in serum at concentrations of 50 ng/mL and 5 ng/mL, respectively. This strategy is helpful for studying the effect of exogenous exposures on human health.
ENVIRONMENTAL POLLUTION
(2023)
Editorial Material
Chemistry, Analytical
Xinyu Liu, Xin Lu, Xianzhe Shi, Guowang Xu
TRAC-TRENDS IN ANALYTICAL CHEMISTRY
(2023)
Article
Cardiac & Cardiovascular Systems
Gaokun Qiu, Yuhui Lin, Yang Ouyang, Mingrong You, Xinjie Zhao, Hao Wang, Rundong Niu, Wending Li, Xuedan Xu, Qi Yan, Yurong Liu, Yingmei Li, Handong Yang, Xiulou Li, Meian He, Xiaomin Zhang, Xiao-Ou Shu, Guowang Xu, Tangchun Wu
Summary: This study aimed to identify metabolites associated with incident acute coronary syndrome (ACS) and explore the causality of these associations. Three metabolites were found to be associated with ACS risk, including one that is a degradation product of a gut-brain peptide, one that is a marker of short-term glycemic excursions, and one that is a very-long-chain saturated fatty acid. These findings highlight the importance of gastrointestinal hormones and glycemic fluctuations in the development of ACS.
JOURNAL OF THE AMERICAN HEART ASSOCIATION
(2023)
Article
Immunology
Xinyu Liu, Congshu Xiao, Pengwei Guan, Qianqian Chen, Lei You, Hongwei Kong, Wangshu Qin, Peng Dou, Qi Li, Yanju Li, Ying Jiao, Zhiwei Zhong, Jun Yang, Xiaolin Wang, Qingqing Wang, Jinhui Zhao, Zhiliang Xu, Hong Zhang, Rongkuan Li, Peng Gao, Guowang Xu
Summary: To control the COVID-19 pandemic, efforts have been made to achieve herd immunity through vaccination since 2020. Unfortunately, most COVID-19 vaccines were approved without a thorough evaluation process. Metabolomic analysis can authentically assess the effects of vaccines by reflecting the responses to stimuli.
FRONTIERS IN IMMUNOLOGY
(2023)
Article
Gastroenterology & Hepatology
Runze Ouyang, Juan Ding, Yan Huang, Fujian Zheng, Sijia Zheng, Yaorui Ye, Qi Li, Xiaolin Wang, Xiao Ma, Yuxin Zou, Rong Chen, Zhihong Zhuo, Zhen Li, Qi Xin, Lina Zhou, Xin Lu, Zhigang Ren, Xinyu Liu, Petia Kovatcheva-Datchary, Guowang Xu
Summary: The gut microbiota plays a crucial role in maintaining host wellbeing by producing various metabolites. The assembly of the gut microbiome is influenced by postnatal factors, but little is known about the development of the gut metabolome. Our study reveals that geography has a significant impact on microbiome dynamics in the first year of life, with major compositional differences observed between Chinese and Swedish cohorts. We found that lipid metabolism, especially acylcarnitines and bile acids, is the most abundant metabolic pathway in the newborn gut, and delivery mode and feeding contribute to differences in the gut metabolome since birth.
