研究领域
研究领域
· 研 究 方 向 ·
1、极端复杂体系分析的方法学研究及其应用：重点开展复杂体系分析中相关基础理论问题的研究；选择性分离介质及预处理技术；复杂体系分析的多维色谱联用技术平台的构建；食品安全等领域的应用。
2、代谢组学平台技术及其应用研究：靶向和非靶向的（多维）色谱-质谱的代谢组学分析新方法。并将其应用于疾病分型、病变标记物发现、中医中药的疗效和毒性评价、植物和微生物次生代谢产物的研究及其生化网络和细胞工厂等研究。
3、转化医学研究：以癌症、糖尿病、肝病等重大疾病为主要研究对象，研究这些重大疾病相关的发病机制和诊疗新方法，包括疾病分型、代谢标志物的发现，以实现重大疾病的早诊、预防及精准治疗。
· Research Interests ·
1. Analytical methods for extremely complex samples and their applications.
2. Metabolomics/metabonomicsanalytical platform and its application in disease biomarker discovery, traditional Chinese medicines, plant functional genome, metabolic networks analysis and reconstruction.
3. Translational Medicine: Focused on major diseases such as cancer, diabetes, liver diseaseetc.
· 代 表 性 工 作 ·
1、代谢组学平台技术及其应用
Method Development and Applications ofMetabolomics
研究重点：发展基于多维及联用技术的色质谱平台，及适用于代谢组学研究的代谢物检测技术和代谢谱表征手段；针对海量数据信息，发展模式识别和数据挖掘技术;并不断的将开发的新技术、新方法固化为标准化的操作流程，推动其在各个领域内的应用。
Our metabolomics research work is focused on the establishment of the analytical platform by using non-targeted and targeted (multi-dimensional) chromatography - mass spectrometry techniques and the development of the bio-informatics method. Based on the standard operation protocols further applications are carried out.
1.1 代谢组学技术平台 Platform ofmetabolomics
Standard operation process of metabolomics |
Integrated analytical platforms with high coverage of the metabolome |
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Excellent quality of biological samples used in metabolomics is the first important factor to make the research results effectively be applied in the clinic. Yin et al.Clin. Chem.2013, 59: 833-845. Liu et al.Clin. Chem.2018,Doi: 10.1373/clinchem.2017.277905. Liu et al.AnalyticaChimicaActa.2018,Doi: 10.1016/j.aca.2018.03.009. |
•GC-MS & GC×GC-MS •RP or HILIC UPLC-MS •2D HPLC-MS •CE-MS •LC-MSlipidomics •Target analysis •LC-MS database of over3000metabolites |
1.2 代谢组学新方法研究 Method development ofMetabolomics
High throughput metabolic profiling methods |
High-quality data acquisition and large-scale metabolic profiling methods for metabolomics |
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An efficient sample preparation on a 96 well filter plate and a rapid LC condition in 12 min, which reduces about 70% of the samples preprocessing time and 60% analysis time. Ouyanget al.Talanta.2018, 185: 483-490. Luo et al.Hepatology.2018, 67:662-675. Liu et al.Clin. Chem.2018,Doi: 10.1373/clinchem.2017.277905. |
Chen et al.Anal. Chem.2013, 85: 8326-8333, Shao etal.J Proteome Res.2015, 14: 906-916. Luo et.al,Anal Chem.2015, 87:5050-5055. Luo et al.J.Chromatogr. A.2016, 1437: 127-136. Zhao et.al,Anal Chem.2016, 88:2234-2242. |
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1.3 代谢组学的应用 Applications ofmetabolomics
Metabolic disorders in malignant tumors and discovery of metabolic markers |
Metabolite function study based on integration of multi-omics analysis |
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Huang et al.Cancer Res.2013, 73: 4992-5002.Luo et al.Hepatology.2018, 67:662-675. |
Ren et al.Mol Cell Proteomics.2016, 15:154-163.Li et al.Sci Rep.2016, 6: 20984. |
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2、复杂样品分离分析的新材料新方法
New methods and materials for complex sample analysis
研究重点：发展基于新型微/纳米材料的样品预处理新方法，提高低丰度代谢物的检测灵敏度；研制离子液体修饰的亲水色谱固定相新材料，提高极性代谢物的分离分析；构建高分辨率高峰容量的新型多维色谱-质谱系统，提高代谢组覆盖度和分离度。
Our research work is focused on the development of new sample pretreatment methods based on novelmicro/nanomaterials for low abundant metabolites. Surfaced-confined ionic liquid stationary phases were synthesized for polar metabolite analysis. Multi-dimensional chromatography- mass spectrometry systems were constructed to extend the coverage of metabolomics.
2.1低丰度代谢物的高选择性富集新材料 Novelenrichment materials for low abundant metabolites
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1.Mesoporous SiO2@ H4/D4taggedazobenene–COOHchemoselectivenanoprobes(mSiO2@azobenzene–COOH) was developedforcomprehensive mapping ofaminometabolitesin complex biological samples with highspecificity and sensitivity. 2.Boronate-decoratedpolyethyleneimine-grafted hybrid magnetic nanoparticles (Fe3O4@SiO2@PEI-FPBA) for highly selective enrichment of60 modifiednucleosides andribosylatedmetabolites from human urine. 3.Highly efficient solid-phase derivatization of sugarphosphates in cellwith titanium-immobilized hydrophilicpolydopamine-coatedsilica. |
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Liet al. Chem.Commun., 2015, 51, 11321-11324; Li et al. Anal. Chem. 2013, 85, 11585−11592 |
Li et al. J.Chromatogr. A 2013 1275: 9-16; Qin et al. J.Chromatogr. A 2016, 1457, 125–133 |
2.2 色谱分离新材料 Novelseparation materials for LC
（1）Surfaced-confinedionic liquid stationary phases(SCILSPs) were developed with a diversity of bonded ligands including single-cationic, multi-cationic,glucaminiumILs by “thiol-ene” clickchemistry. SCILSPspossess mixed-mode retention mechanism and show great prospect for analysis of complexsamples
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Qiaoet al. J.Chromatogr. A 2015, 1396, 62–71;Qiaoet al. J.Chromatogr. A 2014, 1330, 40–50 Qiaoet al. J.Chromatogr. A 2014, 1360, 240–247;Qiaoet al. J.Chromatogr. A2013, 1286, 137–145 Shiet al.J.Chromatogr. A2015, 1420,1–15; Qiaoet al.J.Chromatogr. A2018,doi: 10.016/j.chroma.2017.07.037 |
（2）Novel hybrid monolithic column based on pentafluorobenzyl imidazolium bromide ionic liquid
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Shanet al. J.Chromatogr. A 1375 (2015) 101–109 |
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2.3 多维色谱-质谱系统 Multidimensional chromatography-mass spectrometry
（1）Novel stop-flow 2DLC-MSsystem was constructedforlipidomicsanalysis
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Wang et al.J.Chromatogr. A2013, 1321, 65-72 |
Wang et al. AnalBioanalChem2015, 407, 331-341 |
（2）Novelheart-cutting 2DLC-MSsystems for simultaneous metabolomeandlipidomeanalysisand comprehensiveanalysis of short-, medium- and long-chain acyl-coenzymeAs.
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Wanget al. Anal.Chim.Acta2017, 966,34−40 |
Wang et al. Anal. Chem.2017,89, 12902–12908 |
（3）Novel online 3DLC-MS system bycouplingof pre-separation and comprehensive2DLC forthe separation of complex samples
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Wangetal.Anal. Chem. 2017, 89,1433−1438 |
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3、代谢组学在农业和食品安全中的应用
Metabolomics applications in agricultureand food safety
代谢组学致力于全面、系统地对生物体内的小分子代谢物进行定性和定量分析，从而揭示其生理功能和代谢表型之间的关系。代谢组学在植物生理生化、抗逆胁迫机制及新品种培育及食品安全等领域已有广泛应用。本课题组围绕国家重大需求和领域热点问题开展新方法及其在农业和食品安全等领域应用研究。
Metabolomicsis the unbiased simultaneous identification and quantification of metabolomes. Metabolites are the end products of cellular functions, and their levels can be viewed as the response of biological systems to environmental or genetic manipulation. Metabolicalternations reflectthe changes occurring during plant growth, development, and in response to stress. Metabolomics are aimed at linking between genotypes and phenotypes. Current studies have shown metabolomics can help us to understand the various physiological and biochemical changes occurring in the plants and their influence on the phenotype.
Our research interestsare focused on:
（a）The development of plant metabolomics analytical methods
（2）Metabolomics in assessing plant phenotypes and genetic diversity
（3）Metabolite signatures of genetically modified crops
（4）Metabolomics for plant stressresponse
（5）Metabolomics in food safety
3.1 植物代谢组学分析新方法 Developmentof plant metabolomics analytical methods
Anovel strategyforlarge-scale plantmetabolomics
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Wedevelop a novel correction strategy for large-scale and long-term metabolomics study, which could integrate metabolomics data from multiple batches and different instruments by calibrating gross and systematic errors. The suggested method makes a large amount of metabolomics analysis practicable. |
Zhaoet al.,Anal. Chem.2016, 88, 2234–2242. |
3.2 植物代谢组学应用研究 Metabolomics applications inagriculture
（1）A metabolomics study delineating geographical location-associated primary metabolic changesin plant
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Li et al.,Sci. Rep.2016, 6, 37976 |
Zhao et al.,Aanl.Bioanal. Chem.2018, 410, 839-851 |
（2）Metabolomicsforbiotic and abioticstress responsesin plant
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Qi et al.,Plant Cell & Environment2016, 39, 1749-1766 |
Zhao et al.,Metabolomics2015,11, 1802-1814 |
3.3 食品安全应用研究 Metabolomics applications in food safety
Non-targeted screening method for illegal additives in food matrixes based on UHPLC-HRMS
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Aneffectivenontargetedscreening workflow was developed for detection of illegal additives in the case of fish model. (Fuet al.,Anal. Chem.2016, 88, 8870-8877.) |
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3.4 代谢组学对东亚飞蝗型变物质基础的研究 Metabolomicsanalysis reveals that carnitines are key regulatory metabolites in phase transition of thelocusts
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Adensity-dependent phasepolyphenismofLocustamigratoriawas used as the study model to identify key signaling molecules regulating the expression of phenotypic plasticity.Metabolic analysis based on LC-MS and GC-MSshowed thatsolitariousand gregarious locusts have distinct metabolic profiles in hemolymph. (Wu et al.,PNAS2012, 109, 3259-3263.) |
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