Identifying the compound formulae-related xenobiotics in bio-samples is full of challenges.Conventional strategies always exhibit the insufficiencies in overall coverage,analytical efficiency,and degree of automation,...Identifying the compound formulae-related xenobiotics in bio-samples is full of challenges.Conventional strategies always exhibit the insufficiencies in overall coverage,analytical efficiency,and degree of automation,and the results highly rely on the personal knowledge and experience.The goal of this work was to establish a software-aided approach,by integrating ultra-high performance liquid chromatography/ion-mobility quadrupole time-of-flight mass spectrometry(UHPLC/IM-QTOF-MS)and in-house high-definition MS^(2) library,to enhance the identification of prototypes and metabolites of the compound formulae in vivo,taking Sishen formula(SSF)as a template.Seven different MS2 acquisition methods were compared,which demonstrated the potency of a hybrid scan approach(namely high-definition data-independent/data-dependent acquisition(HDDIDDA))in the identification precision,MS1 coverage,and MS^(2) spectra quality.The HDDIDDA data for 55 reference compounds,four component drugs,and SSF,together with the rat bio-samples(e.g.,plasma,urine,feces,liver,and kidney),were acquired.Based on the UNIFI™platform(Waters),the efficient data processing workflows were established by combining mass defect filtering(MDF)-induced classification,diagnostic product ions(DPIs),and neutral loss filtering(NLF)-dominated structural confirmation.The high-definition MS^(2) spectral libraries,dubbed in vitro-SSF and in vivo-SSF,were elaborated,enabling the efficient and automatic identification of SSF-associated xenobiotics in diverse rat bio-samples.Consequently,118 prototypes and 206 metabolites of SSF were identified,with the identification rate reaching 80.51%and 79.61%,respectively.The metabolic pathways mainly involved the oxidation,reduction,hydrolysis,sulfation,methylation,demethylation,acetylation,glucuronidation,and the combined reactions.Conclusively,the proposed strategy can drive the identification of compound formulae-related xenobiotics in vivo in an intelligent manner.展开更多
根据美国Second Life Library 2.0虚拟社区的建设现状,分析图书馆虚拟社区的营销模式,认为虚拟社区改变了用户被动服务的地位,获得了主动权。对此,图书馆需采用聚众为媒的策略,为虚拟社区中的用户营造良好的使用体验,引导用户成为创建...根据美国Second Life Library 2.0虚拟社区的建设现状,分析图书馆虚拟社区的营销模式,认为虚拟社区改变了用户被动服务的地位,获得了主动权。对此,图书馆需采用聚众为媒的策略,为虚拟社区中的用户营造良好的使用体验,引导用户成为创建服务的合作者和品牌传播的中间人。展开更多
Recent years have witnessed a continuous discovering of new thermoelectric materials which has experienced a paradigm shift from try-and-error efforts to experience-based discovering and first-principles calculation. ...Recent years have witnessed a continuous discovering of new thermoelectric materials which has experienced a paradigm shift from try-and-error efforts to experience-based discovering and first-principles calculation. However, both the experiment and first-principles calculation deriving routes to determine a new compound are time and resources consuming. Here, we demonstrated a machine learning approach to discover new M_(2)X_(3)-type thermoelectric materials with only the composition information. According to the classic Bi_(2)Te_(3) material, we constructed an M_(2)X_(3)-type thermoelectric material library with 720 compounds by using isoelectronic substitution, in which only 101 compounds have crystalline structure information in the Inorganic Crystal Structure Database(ICSD) and Materials Project(MP) database. A model based on the random forest(RF) algorithm plus Bayesian optimization was used to explore the underlying principles to determine the crystal structures from the known compounds. The physical properties of constituent elements(such as atomic mass, electronegativity, ionic radius) were used to define the feature of the compounds with a general formula ^(1)M^(2)M^(1)X^(2)X^(3)X(^(1)M +^(2)M:^(1)X +^(2)X+^(3)X = 2:3). The primary goal is to find new thermoelectric materials with the same rhombohedral structure as Bi_(2)Te_(3) by machine learning.The final trained RF model showed a high accuracy of 91% on the prediction of rhombohedral compounds. Finally, we selected four important features to proceed with the polynomial fitting with the prediction results from the RF model and used the acquired polynomial function to make further discoveries outside the pre-defined material library.展开更多
Objective To construct human myeloma cell cDNA expression library as to screen myeloma tumor antigen. Methods Total RNA and purified mRNA were extracted from human myeloma cell line HMy2. First and second strand cDNA ...Objective To construct human myeloma cell cDNA expression library as to screen myeloma tumor antigen. Methods Total RNA and purified mRNA were extracted from human myeloma cell line HMy2. First and second strand cDNA were synthesized through reverse transcription. After blunting, the cDNA fragments were ligated with EcoR I adapters. Then the cDNAs were digested by Xho I, and smaller than 400bp were removed by Sephacryl-S400 spin column, the remaining were ligated with λZAP vector. The recombinants were packaged in vitro, and a small portion of packaged phage was used to infect E.coli XL1-Blue-MRF for titration. The recombinants were examined by color selection. In order to evaluate the size of cDNA inserts and the diversity of library, the pBK-CMV phagemid were excised from the ZAP express vector by using ExAssist helper phage with XLOLR strain , and then the pBK-CMV phagemid were digested by Xho I and EcoR I. Results The HMy2 cell line cDNA library consisting of 1.58×10 6 recombinant bacteriophages was constructed with the recombinant ratio 99.6%. The average length of the recombinant exogenous inserts was about 1.7kb.Conclusion The constructed cDNA library are deserved to screen target clones.展开更多
Liquid chromatography-mass spectrometry （LC-MS）-based metabolomics has been facilitated by the con- struction of MSz spectral tag （MS2T） library from the total scan ESI MS/MS data, and the development of widely ta...Liquid chromatography-mass spectrometry （LC-MS）-based metabolomics has been facilitated by the con- struction of MSz spectral tag （MS2T） library from the total scan ESI MS/MS data, and the development of widely targeted metabolomics method using MS/MS data gathered from authentic standards. In this report, a novel strategy called step- wise multiple ion monitoring-enhanced product ions （stepwise MIM-EPI） was developed to construct the MS2T library, in which stepwise MIM was used as survey scans to trigger the acquisition of EPI. A total number of 698 （almost） non- redundant metabolites with MS2 spectra were obtained, of which 135 metabolites were identified/annotated. Integrating the data gathered from our MS2T library and other available multiple reaction monitoring （MRM） information, a widely targeted metabolomics method was developed to quantify 277 metabolites, including some phytohormones. Evaluation of the dehydration responses and natural variations of these metabolites in rice leaf not only suggested the coordinated regulation of abscisic acid （ABA） with metabolites such as serotonin derivative（s）, polyamine conjugates under drought stress, but also revealed some C-glycosylated flavones as the potential markers for the discrimination of indica and japonica rice subspecies. The new MS2T library construction and widely targeted metabolomics strategy could be used as a tool for rice functional genomics.展开更多
Volatile organic compounds play essential roles in plant environment interactions as well as determining the fragrance of plants.Although gas chromatography-mass spectrometry-based untargeted metabolo-mics is commonly...Volatile organic compounds play essential roles in plant environment interactions as well as determining the fragrance of plants.Although gas chromatography-mass spectrometry-based untargeted metabolo-mics is commonly used to assess plant volatiles,it suffers from high spectral convolution,low detection sensitivity,a limited number of annotated metabolites,and relatively poor reproducibility.Here,we report a widely targeted volatilomics(WTV)method that involves using a“targeted spectra extraction”algorithm to address spectral convolution,constructing a high-coverage MS2 spectral tag library to expand volatile annotation,adapting a multiple reaction monitoring mode to improve sensitivity,and using regression models to adjust for signal drift.The newly developed method was used to profile the volatilome of rice grains.Compared with the untargeted method,the newly developed WTV method shows higher sensitivity(for example,the signal-to-noise ratio of guaicol increased from 4.1 to 18.8),high annotation coverage(the number of annotated volatiles increased from 43 to 132),and better reproducibility(the number of volatiles in quality control samples with relative standard deviation value below 30.0%increased from 14 to 92 after normalization).Using the WTV method,we studied the metabolic responses of tomato to environmental stimuli and profiled the volatilomes of different rice accessions.The results identified benzothiazole as a potential airborne signal priming tomato plants for enhanced defense and 2-nonanone and 2-heptanone as novel aromatic compounds contributing to rice fragrance.These case studies suggest that the widely targeted volatilomics method is more efficient than those currently used and may considerably promote plant volatilomics studies.展开更多
基金This work was financially supported by National Natural Science Foundation of China(Grant No.:82192914)Tianjin Outstanding Youth Fund(Grant No.:23JCJQJC00030)the Innovation Team and Talents Cultivation Program of National Administration of Traditional Chinese Medicine(Grant No.:ZYYCXTD-C-202009).
文摘Identifying the compound formulae-related xenobiotics in bio-samples is full of challenges.Conventional strategies always exhibit the insufficiencies in overall coverage,analytical efficiency,and degree of automation,and the results highly rely on the personal knowledge and experience.The goal of this work was to establish a software-aided approach,by integrating ultra-high performance liquid chromatography/ion-mobility quadrupole time-of-flight mass spectrometry(UHPLC/IM-QTOF-MS)and in-house high-definition MS^(2) library,to enhance the identification of prototypes and metabolites of the compound formulae in vivo,taking Sishen formula(SSF)as a template.Seven different MS2 acquisition methods were compared,which demonstrated the potency of a hybrid scan approach(namely high-definition data-independent/data-dependent acquisition(HDDIDDA))in the identification precision,MS1 coverage,and MS^(2) spectra quality.The HDDIDDA data for 55 reference compounds,four component drugs,and SSF,together with the rat bio-samples(e.g.,plasma,urine,feces,liver,and kidney),were acquired.Based on the UNIFI™platform(Waters),the efficient data processing workflows were established by combining mass defect filtering(MDF)-induced classification,diagnostic product ions(DPIs),and neutral loss filtering(NLF)-dominated structural confirmation.The high-definition MS^(2) spectral libraries,dubbed in vitro-SSF and in vivo-SSF,were elaborated,enabling the efficient and automatic identification of SSF-associated xenobiotics in diverse rat bio-samples.Consequently,118 prototypes and 206 metabolites of SSF were identified,with the identification rate reaching 80.51%and 79.61%,respectively.The metabolic pathways mainly involved the oxidation,reduction,hydrolysis,sulfation,methylation,demethylation,acetylation,glucuronidation,and the combined reactions.Conclusively,the proposed strategy can drive the identification of compound formulae-related xenobiotics in vivo in an intelligent manner.
基金the National Key Research and Development Program of China (No. 2018YFB0703600)Shenzhen Key Projects of Long-Term Support Plan (No. 20200925164021002)。
文摘Recent years have witnessed a continuous discovering of new thermoelectric materials which has experienced a paradigm shift from try-and-error efforts to experience-based discovering and first-principles calculation. However, both the experiment and first-principles calculation deriving routes to determine a new compound are time and resources consuming. Here, we demonstrated a machine learning approach to discover new M_(2)X_(3)-type thermoelectric materials with only the composition information. According to the classic Bi_(2)Te_(3) material, we constructed an M_(2)X_(3)-type thermoelectric material library with 720 compounds by using isoelectronic substitution, in which only 101 compounds have crystalline structure information in the Inorganic Crystal Structure Database(ICSD) and Materials Project(MP) database. A model based on the random forest(RF) algorithm plus Bayesian optimization was used to explore the underlying principles to determine the crystal structures from the known compounds. The physical properties of constituent elements(such as atomic mass, electronegativity, ionic radius) were used to define the feature of the compounds with a general formula ^(1)M^(2)M^(1)X^(2)X^(3)X(^(1)M +^(2)M:^(1)X +^(2)X+^(3)X = 2:3). The primary goal is to find new thermoelectric materials with the same rhombohedral structure as Bi_(2)Te_(3) by machine learning.The final trained RF model showed a high accuracy of 91% on the prediction of rhombohedral compounds. Finally, we selected four important features to proceed with the polynomial fitting with the prediction results from the RF model and used the acquired polynomial function to make further discoveries outside the pre-defined material library.
文摘Objective To construct human myeloma cell cDNA expression library as to screen myeloma tumor antigen. Methods Total RNA and purified mRNA were extracted from human myeloma cell line HMy2. First and second strand cDNA were synthesized through reverse transcription. After blunting, the cDNA fragments were ligated with EcoR I adapters. Then the cDNAs were digested by Xho I, and smaller than 400bp were removed by Sephacryl-S400 spin column, the remaining were ligated with λZAP vector. The recombinants were packaged in vitro, and a small portion of packaged phage was used to infect E.coli XL1-Blue-MRF for titration. The recombinants were examined by color selection. In order to evaluate the size of cDNA inserts and the diversity of library, the pBK-CMV phagemid were excised from the ZAP express vector by using ExAssist helper phage with XLOLR strain , and then the pBK-CMV phagemid were digested by Xho I and EcoR I. Results The HMy2 cell line cDNA library consisting of 1.58×10 6 recombinant bacteriophages was constructed with the recombinant ratio 99.6%. The average length of the recombinant exogenous inserts was about 1.7kb.Conclusion The constructed cDNA library are deserved to screen target clones.
基金the National High Technology R&D Program of China (863 Program)，the Major State Basic Research Development Program of China (973 Program)，by the National Natural Science Foundation of China，by the Program for New Century Excellent Talents in University of Ministry of Education in China (NCET-09-0401).A patent for this method has been approved by the State Intellectual Property Office of China
文摘Liquid chromatography-mass spectrometry （LC-MS）-based metabolomics has been facilitated by the con- struction of MSz spectral tag （MS2T） library from the total scan ESI MS/MS data, and the development of widely targeted metabolomics method using MS/MS data gathered from authentic standards. In this report, a novel strategy called step- wise multiple ion monitoring-enhanced product ions （stepwise MIM-EPI） was developed to construct the MS2T library, in which stepwise MIM was used as survey scans to trigger the acquisition of EPI. A total number of 698 （almost） non- redundant metabolites with MS2 spectra were obtained, of which 135 metabolites were identified/annotated. Integrating the data gathered from our MS2T library and other available multiple reaction monitoring （MRM） information, a widely targeted metabolomics method was developed to quantify 277 metabolites, including some phytohormones. Evaluation of the dehydration responses and natural variations of these metabolites in rice leaf not only suggested the coordinated regulation of abscisic acid （ABA） with metabolites such as serotonin derivative（s）, polyamine conjugates under drought stress, but also revealed some C-glycosylated flavones as the potential markers for the discrimination of indica and japonica rice subspecies. The new MS2T library construction and widely targeted metabolomics strategy could be used as a tool for rice functional genomics.
基金This work was supported by the Hainan Province Major Research Project(modern agriculture)ZDYF2020066the Hainan Provincial Natural Science Foundation of China(320MS011)the Hainan Major Science and Technology Project(Nno.ZDKJ202002).
文摘Volatile organic compounds play essential roles in plant environment interactions as well as determining the fragrance of plants.Although gas chromatography-mass spectrometry-based untargeted metabolo-mics is commonly used to assess plant volatiles,it suffers from high spectral convolution,low detection sensitivity,a limited number of annotated metabolites,and relatively poor reproducibility.Here,we report a widely targeted volatilomics(WTV)method that involves using a“targeted spectra extraction”algorithm to address spectral convolution,constructing a high-coverage MS2 spectral tag library to expand volatile annotation,adapting a multiple reaction monitoring mode to improve sensitivity,and using regression models to adjust for signal drift.The newly developed method was used to profile the volatilome of rice grains.Compared with the untargeted method,the newly developed WTV method shows higher sensitivity(for example,the signal-to-noise ratio of guaicol increased from 4.1 to 18.8),high annotation coverage(the number of annotated volatiles increased from 43 to 132),and better reproducibility(the number of volatiles in quality control samples with relative standard deviation value below 30.0%increased from 14 to 92 after normalization).Using the WTV method,we studied the metabolic responses of tomato to environmental stimuli and profiled the volatilomes of different rice accessions.The results identified benzothiazole as a potential airborne signal priming tomato plants for enhanced defense and 2-nonanone and 2-heptanone as novel aromatic compounds contributing to rice fragrance.These case studies suggest that the widely targeted volatilomics method is more efficient than those currently used and may considerably promote plant volatilomics studies.
