0 Datasets
0 Files
Get instant academic access to this publication’s datasets.
Yes. After verification, you can browse and download datasets at no cost. Some premium assets may require author approval.
Files are stored on encrypted storage. Access is restricted to verified users and all downloads are logged.
Yes, message the author after sign-up to request supplementary files or replication code.
Join 50,000+ researchers worldwide. Get instant access to peer-reviewed datasets, advanced analytics, and global collaboration tools.
✓ Immediate verification • ✓ Free institutional access • ✓ Global collaborationJoin our academic network to download verified datasets and collaborate with researchers worldwide.
Get Free AccessAbstract Arsenic is a metalloid toxic to plants, animals and human beings. Small ubiquitin-like modifier (SUMO) conjugation is involved in many biological processes in plants. However, the role of SUMOylation in regulating plant arsenic response is still unclear. In this study, we found that dysfunction of SUMO E3 ligase SIZ1 improves arsenite resistance in Arabidopsis. Overexpression of the dominant-negative SUMO E2 variant resembled the arsenite-resistant phenotype of siz1 mutant, indicating that SUMOylation plays a negative role in plant arsenite detoxification. The siz1 mutant accumulated more glutathione (GSH) than the wild type under arsenite stress, and the arsenite-resistant phenotype of siz1 was depressed by inhibiting GSH biosynthesis. The transcript levels of the genes in the GSH biosynthetic pathway were increased in the siz1 mutant comparing with the wild type in response to arsenite treatment. Taken together, our findings revealed a novel function of SIZ1 in modulating plant arsenite response through regulating the GSH-dependent detoxification.
Jian Kang Zhu, Zhen Wang, Yechun Hong, Yunjuan Chen, Huazhong Shi, Xiangfeng Kong, Juanjuan Yao, Mingguang Lei (2022). SUMO E3 ligase SIZ1 negatively regulates arsenite resistance via depressing GSH biosynthesis in Arabidopsis. , 2(1), DOI: https://doi.org/10.1007/s44154-021-00029-8.
Datasets shared by verified academics with rich metadata and previews.
Authors choose access levels; downloads are logged for transparency.
Students and faculty get instant access after verification.
Type
Article
Year
2022
Authors
8
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.1007/s44154-021-00029-8
Access datasets from 50,000+ researchers worldwide with institutional verification.
Get Free Access