Hongzhong Lu

  • Tel: +86-021
  • Email: hongzhonglu@sjtu.edu.cn
  • Address: 800 Dongchuan RD. Minhang District, Shanghai, China
  • Focused on digital modeling and characterization of cell metabolism network , and applied the latest multi-dimensional cell metabolic model in the area of intelligent strain design and biological big data analysis. Relevant achievements have been successively published in journals like Nat Commun、Mol Syst Biol, et al.

Education and Research Experience

  • 2021.09- , Tracked Associated Professor, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University (SJTU).
  • 2021.01-2021.09 Researcher, Department of molecular and clinical medicine, University of Gothenburg. Supervisor: Prof. Fredrik Bäckhed.
  • 2017.09-2020.12 Post-Doc Researcher, Department of Biology and Biological Engineering, Chalmers University of Technology. Supervisor: Prof. Jens Nielsen.
  • 2016.06-2017.09, Associate scientist, DSM, Shanghai, China
  • 2010.09-2016.6, PhD in major of Biochemical Engineering, State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology (ECUST), China. Research field: Systems biology, Supervisor: Prof. Siliang Zhang and Prof. Ju Chu
  • PhD thesis title: Integrating 13C labelled flux analysis with genome scale metabolic model simulation to probe the mechanism underlying the high-yield production of enzymes by Aspergillus niger.
  • 2006.09-2010.06, Bachelor in major of Biological Science, Sichuan University, China.

Research Interests

Reconstruction and applications of whole-cell models

Focusing on yeast, mutiple state of art techonologies including systematic integration of multi-scale omics, machine learning to develop the next generation of whole-cell models, which will be as a strong platform to promote the research in system biology and synthetic biology.

In silico cell factory design

By combining rational prediction from metabolic models with quantitative analysis of proteomics, fluxomics and metabolomics, we will accelerate the development of high-performance industrial strains by remodeling the distribution of resource and fluxes within the target cell factories.

Systematic evolution analysis of yeast

In a sytematic way, we will explore the evolutionary origin of yeast diverse metabolic function and traits through the integrative analysis from model prediction, comparative genomics and physiological study.

Selected Publications

  • •  

    Yuan L, Lu H* (co-corresponding author), Li F, Nielsen J and Kerkhoven* EJ. HGTphyloDetect: facilitating the identification and phylogenetic analysis of horizontal gene transfer. Briefings in Bioinformatics, 2023: 1–7.


    Lu H, Kerkhoven EJ, Nielsen J. Multiscale models quantifying yeast physiology: towards a whole-cell model. Trends in Biotechnology, 2022, 40(3):291-305.


    Lu H#, Li F#, Yuan L#, Domenzain I, Yu R, Wang H, Li G, Chen Y, Ji B, Kerkhoven EJ, Nielsen J*. Yeast metabolic innovations emerged via expanded metabolic network and gene positive selection. Molecular Systems Biology, 2021(17):e10427.


    Lu H#, Li F#, Sánchez BJ, Zhu Z, Li G, Domenzain I, Marcišauskas S, Anton PM, Lappa D, Lieven C, Beber ME, Sonnenschein N, Kerkhoven EJ, Nielsen J*. A consensus S. cerevisiae metabolic model Yeast8 and its ecosystem for comprehensively probing cellular metabolism. Nature Communications, 2019, 10 (1):1-13.


    Lu H, Chen Y, Nielsen J, Kerkhoven EJ. Kinetic Models of Metabolism. Metabolic Engineering: Concepts and Applications, 2021 (13): 153-170. Book chapter.

  • •  

    Lu H, Liu X, Huang M*, Xia J, Chu J*, Zhuang Y, Zhang S, Noorman H. Integrated isotope-assisted metabolomics and (13)C metabolic flux analysis reveals metabolic flux redistribution for high glucoamylase production by Aspergillus niger. Microb Cell Fact, 2015(14):147.


    Lu H, Cao W, Ouyang L, Xia J, Huang M* , Chu J*, Zhuang Y, Zhang S, Noorman H. Comprehensive reconstruction and in silico analysis of Aspergillus niger genome-scale metabolic network model that accounts for 1210 ORFs. Biotechnology and Bioengineering, 2017, 114(3):685-695.


    Lu H#, Cao W#, Liu X, Sui Y, Ouyang L*, Xia J, Huang M, Zhuang Y, Zhang S, Noorman H, Chu J*. Multi-omics integrative analysis with genome-scale metabolic model simulation reveals global cellular adaptation of Aspergillus niger under industrial enzyme production condition. Sci Rep, 2018, 8(1):14404.

  • Participated in two EU’s Horizon 2020 program -Bioinformatics Services for Data-Driven Design of Cell Factories and Communities (No 686070)以及Model-Based Construction And Optimisation Of Versatile Chassis Yeast Strains For Production Of Valuable Lipid And Aromatic Compounds (No 720824).

Selected Grants