zhijin gong

Dr. zhijin gong


Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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16 February 2023 in Microorganisms
Verified
Journal Article
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ZGzhijin gong
zhijin gong
RXRong Xie
Rong Xie
YZYang Zhang
Yang Zhang
MWMeng Wang
Meng Wang
TTTianwei Tan
Tianwei Tan
The development of MFC using electroactive industrial microorganisms has seen a surge of interest because of the co-generation for bioproduct and electricity production. Vibrio natriegens as a promising next-generation industrial microorganism chassis and its application for microbial fuel cells (MFC) was first studied. Mediated electron transfer was found in V. natriegens MFC (VMFC), but V. natriegens cannot secrete sufficient electron mediators to transfer electrons to the anode. All seven electron mediators supplemented are capable of improving the electronic transfer efficiency of VMFC. The media and carbon sources switching study reveals that VMFCs have excellent bioelectricity generation performance with feedstock flexibility and high salt-tolerance. Among them, 1% glycerol as the sole carbon source produced the highest power density of 111.9 ± 6.7 mW/cm2. The insight of the endogenous electronic mediators found that phenazine-1-carboxamide, phenazine-1-carboxylic acid, and 1-hydroxyphenazine are synthesized by V. natriegens via the shikimate pathway and the phenazine synthesis and modification pathways. This work provides the first proof for emerging industrial biotechnology chassis V. natriegens as a novel high salt-tolerant and feedstock flexibility electroactive microorganism for MFC, and giving insight into the endogenous electron mediator biosynthesis of VMFC, paving the way for the application of V. natriegens in MFC and even microbial electrofermentation (EF).

25 May 2022 in Microorganisms
Verified
Journal Article
Open access
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ZGzhijin gong
zhijin gong
QHQiuhong He
Qiuhong He
JLJinfeng Liu
Jinfeng Liu
JZJing Zhou
Jing Zhou
CCChengchuan Che
Chengchuan Che
GYGe Yang
Ge Yang
The rhamnolipid production of Pseudomonas aeruginosa has been impeded by its severe foaming; overcoming the bottleneck of foaming has become the most urgent requirement for rhamnolipid production in recent decades. In this study, we performed rhamnolipid fermentation under weakly acidic conditions to address this bottleneck. The results showed that the foaming behavior of rhamnolipid fermentation broths was pH-dependent with the foaming ability decreasing from 162.8% to 28.6% from pH 8 to 4. The “non-foaming” rhamnolipid fermentation can be realized at pH 5.5, but the biosynthesis of rhamnolipids was significantly inhibited. Further, rhamnolipid yield rebounded from 8.1 g/L to 15.4 g/L after ultraviolet and ethyl methanesulfonate compound mutagenesis. The mechanism study showed that the species changes of rhamnolipid homologs did not affect the foaming behavior of the fermentation but had a slight effect on the bioactivity of rhamnolipids. At pH 8.0 to 5.0, increased surface tension, decreased viscosity and zeta potential, and aggregation of rhamnolipid molecules contributed to the “non-foaming” rhamnolipid fermentation. This study provides a promising avenue for the “non-foaming” rhamnolipid fermentation and elucidates the mechanisms involved, facilitating the understanding of pH-associated foaming behavior and developing a more efficient strategy for achieving rhamnolipid production.

21 September 2023 in Fermentation
Verified
Journal Article
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YZYang Zhang
Yang Zhang
BCBingqi Cai
Bingqi Cai
MLMeng Liu
Meng Liu
KHKeqin He
Keqin He
ZGzhijin gong
zhijin gong
TTTianwei Tan
Tianwei Tan
The green biosynthesis of adipic acid, an important monomer of nylon 6,6, has become a research hotspot. α-Aminoadipate is a key intermediate in the metabolic pathway that converts L-lysine to produce adipic acid. In addition, metabolic flux analysis has become an important part of metabolic engineering. Many metabolic optimization algorithms have been developed to predict engineering intervention strategies with the aim of improving the production of target chemicals. Here, OptHandle, a new metabolic optimization algorithm, has been developed. And, we use OptHandle to optimize the biosynthesis of α-aminoadipate. Based on the results of OptHandle, an engineered Escherichia coli with a 13-fold higher titer was obtained, and 1.10 ± 0.02 g/L of α-aminoadipate was produced. The efficient synthesis of α-aminoadipate lays a foundation for the green production of adipic acid.