王 冠
生物工程专业:硕士生导师
生物化工专业:硕士生导师
生物与医药专业(生物工程领域):硕士生导师
王冠,工学博士,副教授,硕士生导师。先后入选1066vip威尼斯官网“青年英才培育计划” (2020 A类),上海市青年科技启明星(2021A类),全国石油和化工优秀教学团队(2023年)。2018年毕业于1066vip威尼斯官网获生物化工专业工学博士学位,同年进入1066vip威尼斯官网轻工技术与工程流动站从事博士后研究工作,2020年7月出站担任教职。
依托生物反应器工程国家重点实验室和国家生化工程技术研究中心(上海),近年来围绕微生物发酵过程共性关键技术开发与应用,聚焦微生物细胞代谢建模、工业规模不均匀流场环境理性缩放、“细胞-环境”互作代谢机制解析以及工业规模发酵过程理性设计与评估,提出了基于细胞代谢动力学-流体力学模型整合下工业生物过程理性放大新方法。作为项目负责人主持国家自然科学基金青年基金、国家重点研发计划子课题、上海市“科技创新行动计划”启明星项目、上海市“科技创新行动计划”自然科学基金、上海市促进人才发展专项资金(博士后日常经费)等项目;作为主要项目骨干参与中国-荷兰国际科技合作专项和多项国家自然科学基金项目等。2015年赴荷兰代尔夫特理工大学(Delft University of Technology)皇家科学院院士Prof. Joseph J. Heijnen课题组开展合作项目 “Bioreactor scale-down”相关实验以及定量代谢物组学分析技术交流与学习。
近年来,在Trends in Biotechnology, Bioresource Technology, Biotechnology and Bioengineering, Microbial Biotechnology, Biotechnology Journal, Journal of Biotechnology等本领域权威期刊上发表SCI收录论文25篇,第一或通讯作者20篇,英文专著3章节,申请中国发明专利14项。受邀担任Bioengineering专刊“Design, Optimization and Scale Up of Fermentation Processes” Guest editor以及该期刊Topical Advisory Panel Members。Biotechnology and Bioengineering, Biotechnology Journal, Journal of Biotechnology, Biochemical Engineering Journal, Process Biochemistry, Metabolites, Engineering in Life Sciences等期刊审稿人。
在学生培养上,2020年晋升硕导以来,累计指导硕士毕业5人,本科生毕业9人。其中7人次荣获研究生国家奖学金、研究生计划外奖学金、上海市优秀毕业生、校优秀本科生毕业论文等荣誉;指导研究生和本科生参加“挑战杯”、“全国大学生生命科学竞赛”、“互联网+”等全国性创新创业大赛,通过竞赛训练学生的科研思维和培养实践能力,目前已带领相关同学2次获上海市市级及以上奖项。
研究方向:
[1] 工业规模生物反应器不均匀流场理性缩放与细胞代谢调控机制解析
大规模生物反应器内“细胞运动轨迹”模拟与多组学整合分析
[2] 大数据-代谢模型驱动下的生物过程智能优化与调控
基于大数据-机理融合驱动模型实现发酵过程跨尺度智能优化与调控
[3] 肿瘤细胞代谢与靶向治疗
靶向肿瘤细胞代谢并结合肿瘤药物定点智能控释系统实现“自杀式”肿瘤治疗
[4] 哺乳动物细胞培养过程优化与放大
基于过程分析技术(PAT)的哺乳动物细胞培养工艺开发与应用
主持或参加的科研项目或基金:
[1] 上海市青年科技启明星计划A类,项目负责人
[2] “绿色生物制造” 国家重点研发计划子课题1,项目负责人
[3] “绿色生物制造” 国家重点研发计划子课题2,项目负责人
[4] 国家自然科学基金青年基金项目,项目负责人
[5] 上海市自然科学基金项目,项目负责人
[6] 上海市促进人才发展专项资金-博士后日常经费,项目负责人
[7] 上海市生物过程工程服务平台能力建设专项,项目骨干
[8] 国家自然科学基金面上基金项目,项目骨干
[9] 国家自然科学基金青年基金项目,项目骨干
[10]中国-荷兰国际科技合作计划,项目骨干
本科与研究生教学:
[1] 本科生专业必修课,《实验数据统计分析》,16学时,1学分;
[2] 本科生专业必修课,《生物反应工程原理》(全英文),48学时,3学分;
[3] 本科生专业必修课,《智能生物制造医药与设计》,16/48学时,3学分
[4] 研究生专业核心课,《生物反应器工程》,16/64学时,4学分;
[5] 研究生专业选修课,《生物反应工程》(全英文),32学时,2学分。
代表性论文(*通讯作者):
1)一作或通讯论文
[1] Jiachen Zhao, Muhammad Alkali Muawiya, Yingping Zhuang, Guan Wang*.Developing rational scale-down simulators for mimicking substrate heterogeneities based on cell lifelines in industrial-scale bioreactors. Bioresource Technology, 2024, 395, 130354.
[2] Zhongyi Zhang, Qingchao Jiang*, Guan Wang*, Chunjian Pan, Zhixing Cao, Xuefeng Yan, Yingping Zhuang. Neural networks-based hybrid beneficial variable selection and modeling for soft sensing. Control Engineering Practice, 2023, 139, 105613.
[3] Ziyu Zhu, Xiaoqian Chen, Wenhao Li, Yingping Zhuang, Yuzheng Zhao, Guan Wang*. Understanding the effect of temperature downshift on CHO cell growth, antibody titer and product quality by intracellular metabolite profiling and in vivo monitoring of redox state. Biotechnology Progress, 2023, 39(4), e3352.
[4] Tong Wang, Xueting Wang, Yingping Zhuang, Guan Wang*. A systematic evaluation of quenching and extraction procedures for quantitative metabolome profiling of HeLa carcinoma cell under 2D and 3D cell culture conditions. Biotechnology Journal, 2023, 18(5), 2200444.
[5] Qi Yang, Wenli Lin, Jiawei Xu, Nan Guo, Jiachen Zhao, Gaoya Wang, Yongbo Wang, Ju Chu, and Guan Wang*. Changes in oxygen availability during glucose-limited chemostat cultivations of Penicillium chrysogenum lead to rapid metabolite, flux and productivity responses.Metabolites, 2022, 12(1), 45.
[6] Lin Wang, Xueting Wang, Tong Wang, Yingping Zhuang, and Guan Wang*. Multi-omics analysis defines 5-fluorouracil drug resistance in 3D HeLa carcinoma cell model. Bioresources and Bioprocessing,2021, 8(1), 1-21.
[7] Guan Wang*, Cees Haringa, Henk Noorman, Ju Chu, and Yingping Zhuang*. Developing a computational framework to advance bioprocess scale-up. Trends in Biotechnology, 2020, 38(8), 846-856.
[8] Guan Wang, Cees Haringa, Wenjun Tang, Henk Noorman, Ju Chu*, Yingping Zhuang*, and Siliang Zhang. Coupled metabolic-hydrodynamic modeling enabling rational scale-up of industrial bioprocesses. Biotechnology and Bioengineering, 2020, 117, 844-867.
[9] Tong Wang, Lin Wang, Guan Wang*, and Yingping Zhuang*. Leveraging and manufacturing in vitro multicellular spheroid-based tumor cell model as a preclinical tool for translating dysregulated tumor metabolism into clinical targets and biomarkers. Bioresources and Bioprocessing, 2020,7(1), 1-34.
[10] Jiachen Zhao, Guan Wang*, Ju Chu, and Yingping Zhuang. Harnessing microbial metabolomics for industrial applications. World Journal of Microbiology and Biotechnology, 2020, 36(1), 1-18.
[11] Guan Wang*, Ju Chu, Yingping Zhuang*, Walter van Gulik, and Henk Noorman. A dynamic model-based preparation of uniformly-13C-labeled internal standards facilitates quantitative metabolomics analysis of Penicillium chrysogenum. Journal of Biotechnology, 2019, 299, 21-31.
[12] Guan Wang, Xinxin Wang, Tong Wang, Walter van Gulik, Henk J. Noorman, Yingping Zhuang*, Ju Chu*, and Siliang Zhang. Comparative fluxome and metabolome analysis of formate as an auxiliary substrate for penicillin production under glucose-limited cultivation of Penicillium chrysogenum. Biotechnology Journal, 2019, 14(10), 1900009.
[13] Guan Wang, Junfei Zhao, Xinxin Wang, Tong Wang, Yingping Zhuang*, Ju Chu*, Siliang Zhang, Henk J. Noorman. Quantitative metabolomics and metabolic flux analysis reveal impact of altered trehalose metabolism on metabolic phenotypes of Penicillium chrysogenum in aerobic glucose-limited chemostats, Biochemical Engineering Journal, 2019, 146: 41-51.
[14] Guan Wang, Baofeng Wu, Junfei Zhao, Cees Haringa, Jianye Xia, Ju Chu*, Yingping Zhuang, Siliang Zhang, Joseph J. Heijnen, Walter van Gulik, Amit T. Deshmukh, Henk J. Noorman*. Power input effects on degeneration in prolonged penicillin chemostat cultures: A systems analysis at flux, residual glucose, metabolite, and transcript levels, Biotechnology and Bioengineering, 2018, 115: 114-125.
[15] Guan Wang, Junfei Zhao, Cees Haringa, Wenjun Tang, Jianye Xia, Ju Chu*, Yingping Zhuang, Siliang Zhang, Amit T. Deshmukh, Walter van Gulik, Joseph J. Heijnen, Henk J. Noorman. Comparative performance of different scale-down simulators of substrate gradients in Penicillium chrysogenum cultures: the need of a biological systems response analysis, Microbial Biotechnology, 2018, 11: 486-497.
[16] Guan Wang, Wenjun Tang, Jianye Xia, Ju Chu*, Henk J. Noorman, Walter van Gulik. Integration of microbial kinetics and fluid dynamics toward model-driven scale-up of industrial bioprocesses, Engineering in Life Sciences, 2015, 15: 20-29.
[17] Guan Wang, Ju Chu*, Henk J. Noorman, Jianye Xia, Wenjun Tang, Yingping Zhuang, Siliang Zhang. Prelude to rational scale-up of penicillin production: a scale-down study, Applied Microbiology and Biotechnology, 2014, 98: 2359-2369.
2)合著论文
[18] Li, Xinzhe, Yufeng Dong, Lu Chang, Lifan Chen, Guan Wang, Yingping Zhuang, and Xuefeng Yan*. Dynamic hybrid modeling of fuel ethanol fermentation process by integrating biomass concentration XGBoost model and kinetic parameter artificial neural network model into mechanism model. Renewable Energy, 2023, 205, 574-582.
[19] Jianye Xia, Guan Wang, Meng Fan, Min Chen, Zeyu Wang, and Yingping Zhuang*. Understanding the scale-up of fermentation processes from the viewpoint of the flow field in bioreactors and the physiological response of strains. Chinese Journal of Chemical Engineering, 2021, 30, 178-184.
[20] Weiqiang Cao, Guan Wang, Hongzhong Lu, Liming Ouyang*, Ju Chu, Yufei Sui, and Yingping Zhuang*. Improving cytosolic aspartate biosynthesis increases glucoamylase production in Aspergillus niger under oxygen limitation. Microbial Cell factories, 2020, 19: 1-14.
[21] Shaohuang Shen, Guan Wang, Ming Zhang, Yin Tang, Yang Gu, Weihong Jiang, Yonghong Wang* and Yingping Zhuang*. Effect of temperature and surfactant on biomass growth and higher-alcohol production during syngas fermentation by Clostridium carboxidivorans P7. Bioresources and Bioprocessing, 2020, 7(1), 1-13.
[22] Cees Haringa, Wenjun Tang, Guan Wang, Amit T. Deshmukh, Wouter A van Winden, Ju Chu, Walter M van Gulik, Joseph J Heijnen, Robert Mudde and Henk J Noorman*. Computational fluid dynamics simulation of an industrial P. chrysogenum fermentation with a coupled 9-pool metabolic model: Towards rational scale-down and design optimization, Chemical Engineering Science, 2018, 175: 12-24.
[23] Wenjun Tang, Amit T. Deshmukh, Cees Haringa, Guan Wang, Walter van Gulik, Wouter van Winden, Matthias Reuss, Joseph J. Heijnen, Jianye Xia, Ju Chu* and Henk J. Noorman. A 9-pool metabolic structured kinetic model describing days to seconds dynamics of growth and product formation by Penicillium chrysogenum, Biotechnology and Bioengineering, 2017, 114: 1733-1743.
[24] 王冠,田锡炜,夏建业,储炬,张嗣良,庄英萍*. 大数据-模型混合驱动下生物过程优化与放大的新机遇与挑战. 生物工程学报,2021, 37(3), 1004-1016.
[25] 朱紫瑜,王冠,庄英萍*. 大规模哺乳动物细胞培养工程的现状与展望. 合成生物学,2021, 2, 1-23.
[26] 田锡炜,王冠,张嗣良,庄英萍*. 工业生物过程智能控制原理和方法进展. 生物工程学报,2019, 35(10), 2014-2024.
[27] 赵骏飞, 王冠, 吴宝峰, 储炬*, 张嗣良. 基于土壤农杆菌转化法高效构建高产产黄青霉tps1 和tps2 敲除菌株. 中国医药工业杂志,2017, 48(9), 1293-1301.
撰写专著:
[1] Guan Wang, Ali Mohsin, Ju Chu, Yingping Zhuang, Siliang Zhang. Advances and prospects for advanced biomanufacturing, in Book “Scale-up and Chemical Process for Microbial Production of Plant-Derived Bioactive Compounds”, Elsevier, 2024, in press.
[2] Guan Wang*, Cees Haringa, Ju Chu, Yingping Zhuang, Wouter van Winden, Henk Noorman. Harnessing dynamic metabolomics for bioprocess prediction and beyond.Handbook of Molecular Biotechnology, CRC press, 2024, in press.
[3] Xia JY, Guan Wang, Jihan Lin, Yonghong Wang, Ju Chu, Yingping Zhuang, SiLiang Zhang*. Advances and practices of bioprocess scale-up. Bioreactor Engineering Research and Industrial Applications II: Springer. 2015, p 137-151.
发明专利:
[1]王冠,陈力凡,王勇博,王雪婷,王高雅,张丽娜,于晓飞,庄英萍. 一种提升酿酒酵母高乙醇耐受性能的动态适应性进化方法及其厌氧恒化培养装置202311127294X
[2] 王冠,许之贤,祝晓丰,郭美锦. 一种基于机器学习的质粒发酵变温过程预测方法及系统CN202310411779.5
[3] 王冠,王勇博,于晓飞,黄雨,陈力凡,庄英萍. 一种厌氧乙醇发酵过程中物质反应速率的预测方法 CN202310466275.3
[4] 王冠,郭中方,陈晓倩,刘寅寅,李兆君,梅奕晨,姜欣瑜,翁翊轩,王彤,赵玉政,庄英萍. 一种基于胞内氧化还原探针的抗肿瘤药物代谢评估和筛选方法 2023107015539
[5] 王冠,郭中方,刘寅寅,李兆君,姜欣瑜,张未,梅奕晨,翁翊轩,王彤,庄英萍. 一种基于三维肿瘤球体模型的多尺度抗肿瘤药物筛选方法202311549125.5
[6] 王冠, 王彤, 王琳, 欧阳立明, 庄英萍. 一种多细胞肿瘤球及其高通量制备方法CN110616185A
[7] 王冠, 赵佳晨, 朱慧东, 林文莉, 徐嘉蔚, 郭楠, 庄英萍. 用于工业规模生物反应器内流场环境缩放设计的方法及系统CN202210137282.4
[8] 颜学峰, 李欣喆, 董裕峰, 王冠, 常璐, 陈力凡, 田锡炜, 庄英萍. 燃料乙醇发酵过程菌丝体浓度、乙醇浓度和葡萄糖浓度时间序列预测方法CN202210921099.3
[9] 田锡炜, 常璐, 王冠, 陈力凡, 庄英萍, 张志凌, 刘晓峰, 刘劲松, 邓立康, 林海龙, 刘新颖, 邵玉彬, 田晓俊. 一种利用酿酒酵母发酵生产乙醇的方法CN202210752551.8
[10] 颜学峰, 康叶茗, 董裕峰, 卢伟鹏, 庄英萍, 邓立康, 田晓俊, 刘晓峰, 刘小辰, 张志凌, 田锡炜, 王冠, 孙新通, 范新龙, 刘新颖, 从志会. 燃料乙醇发酵过程工业知识图谱构建方法CN202110722594.7
[11] 颜学峰, 卢伟鹏, 庄英萍, 邓立康, 田晓俊, 刘晓峰, 刘小辰, 张志凌, 田锡炜, 董裕峰, 王冠, 孙新通, 范新龙, 刘新颖, 从志会. 燃料乙醇生产状态可视化在线监测方法CN202110717333.6
[12] 林海龙, 颜学峰, 董裕峰, 卢伟鹏, 刘劲松, 庄英萍, 邓立康, 田锡炜, 田晓俊, 刘晓峰, 王冠, 王梦. 发酵罐乙醇出罐浓度的预测方法、控制装置、及存储介质CN202110573442.5
[13] 田锡炜, 庄英萍, 冯瑶, 林海龙, 陈阳, 王泽宇, 王冠, 王海艺. 一种基于在线电容值监测的葡萄糖补料发酵生产乙醇的方法CN202011605264.1
[14] 田锡炜, 庄英萍, 冯瑶, 陈阳, 王泽宇, 王冠, 王海艺. 一种基于在线乙醇浓度响应值监测的葡萄糖补料发酵生产乙醇的方法CN202011606657.4
联系方式:
上海市徐汇区梅陇路130号邮编200237
办公室:实验十八楼411室
电话:021-64250719
邮箱:guanwang@ecust.edu.cn