Dedicated to the development of enabling technologies in synthetic biology, our focus lies in the efficient screening and engineering of microbial cell factories. We employ high-throughput sequencing methods, coupled with metabolic engineering and high-throughput screening techniques, to design and utilize high-throughput exploration and engineering techniques for gene transcription and translation elements, regulatory factors, and functional enzyme components. This approach enables the deciphering of the working mechanisms and regulatory pathways of genes in transcription, translation, and metabolic pathways. Furthermore, we utilize artificial intelligence technologies such as machine learning to assist in the design and transformation of key enzymes and biosynthetic pathways. This comprehensive strategy allows for the efficient production of bulk chemicals and proteins by industrial microorganisms.

Education

2009.09 – 2015.06 Ph.D. in Microbiology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, China

2005.09 – 2009.07 B.S. in Biological Engineering, Harbin Institute of Technology, China

Professional Experience

2021.12 – present, Investigator, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, China

2019.01 – 2021.10, Postdoctoral Fellow in Mikhail Kashlev’s group, National Institutes of Health/National Cancer Institute, USA

2015.06 – 2018.12, Postdoctoral Fellow in Ding Jun Jin’s group, National Institutes of Health/National Cancer Institute, USA

Publication Records

(^#, equal contribution; *, corresponding author)

1. Sun Z, Yakhnin AV, FitzGerald PC, Mclntosh CE, Kashlev M*. Nascent RNA sequencing identifies a widespread sigma70 dependent pausing regulated by Gre factors in bacteria. Nature Communications, 2021. 12: 906.

2. Franco KS^#, Sun Z^#, Chen Y, Cagliero C, Zuo Y, Zhou YN, Kashlev M, Jin DJ, Schneider TD*. Escherichia coli σ38 promoters use two UP elements instead of a −35 element: resolution of a paradox and discovery that σ38 transcribes ribosomal promoters. BioRxiv, 2020.

3. Sun Z, Cagliero C, Izard J, Chen Y, Zhou YN, Heinz WF, Schneider TD and Jin DJ*. Density of σ70 promoter-like sites in the intergenic regions dictates the redistribution of RNA polymerase during osmotic stress in Escherichia coli. Nucleic Acids Research, 2019. 47(8): 3970–3985.

4. Martin CM, Sun Z, Zhou YN and Jin DJ*. Extrachromosomal nucleolus-like compartmentalization by a plasmid-borne ribosomal RNA operon and its role in nucleoid compaction. Frontiers in Microbiology, 2018. 9: 1115.

5. Martin CM, Cagliero C, Sun Z, Chen D, and Jin DJ*. Imaging of transcription and replication in the bacterial chromosome with multicolor Three-Dimensional Superresolution Structured Illumination Microscopy. Methods in Molecular Biology, 2018. 1837: 117–129.

6. Li J^#, Wang C^#, Yang G, Sun Z, Guo H, Shao K, Gu Y, Jiang W* and Zhang P*. Molecular mechanism of environmental d-xylose perception by a XylFII-LytS complex in bacteria. PNAS, 2017. 114(31): 8235–8240.

7. Jin DJ*, Martin CM, Sun Z, Cagliero C and Zhou YN. Nucleolus-like compartmentalization of the transcription machinery in fast-growing bacterial cells. Critical Reviews in Biochemistry and Molecular Biology, 2016. 52(1): 96–106.

8. Sun Z, Chen Y, Yang C, Yang S, Gu Y* and Jiang W*. A novel three-component system-based regulatory model for D-xylose sensing and transport in Clostridium beijerinckii. Molecular Microbiology, 2015. 95(4): 576–589.

9. Gu Y^#, Ding Y^#, Ren C, Sun Z, Rodionov DA, Zhang W, Yang S, Yang C* and Jiang W*. Reconstruction of xylose utilization pathway and regulons in Firmicutes. BMC Genomics, 2011. 11: 255.

Patents

Yang Gu, Han Xiao, Weihong Jiang, Yuanyuan Ning, Zhilin Li, Yu Jiang, Zhe Sun, Sheng Yang. Method for improving sugar utilization rate of Clostridium acetobutylicum in mixed sugar fermentation. CN. ZL201210163123.8.

Dedicated to the development of enabling technologies in synthetic biology, our focus lies in the efficient screening and engineering of microbial cell factories. We employ high-throughput sequencing methods, coupled with metabolic engineering and high-throughput screening techniques, to design and utilize high-throughput exploration and engineering techniques for gene transcription and translation elements, regulatory factors, and functional enzyme components. This approach enables the deciphering of the working mechanisms and regulatory pathways of genes in transcription, translation, and metabolic pathways. Furthermore, we utilize artificial intelligence technologies such as machine learning to assist in the design and transformation of key enzymes and biosynthetic pathways. This comprehensive strategy allows for the efficient production of bulk chemicals and proteins by industrial microorganisms.