Hong Li

Dr. Hong Li

orcid

Research Focus & Metrics

Academic Career Length

17Years (2010-Present)

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

Representative Publications

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6 February 2020 in BMC Plant Biology
Verified
Journal Article
Open access
PDF file
XYXiaodi Yang
Xiaodi Yang
SYShiping Yang
Shiping Yang
HQHuan Qi
Huan Qi
TWTianPeng Wang
TianPeng Wang
HLHong Li
Hong Li
ZZZiding Zhang
Ziding Zhang
Background: Protein-protein interactions (PPIs) play very important roles in diverse biological processes. Experimentally validated or predicted PPI data have become increasingly available in diverse plant species. To further explore the biological functions of PPIs, understanding the interaction details of plant PPIs (e.g., the 3D structural contexts of interaction sites) is necessary. By integrating bioinformatics algorithms, interaction details can be annotated at different levels and then compiled into user-friendly databases. In our previous study, we developed AraPPISite, which aimed to provide interaction site information for PPIs in the model plantArabidopsis thaliana. Considering that the application of AraPPISite is limited to one species, it is very natural that AraPPISite should be evolved into a new database that can provide interaction details of PPIs in multiple plants.Description: PlaPPISite (http://zzdlab.com/plappisite/index.php) is a comprehensive, high-coverage and interaction details-oriented database for 13 plant interactomes. In addition to collecting 121 experimentally verified structures of protein complexes, the complex structures of experimental/predicted PPIs in the 13 plants were also constructed, and the corresponding interaction sites were annotated. For the PPIs whose 3D structures could not be modelled, the associated domain-domain interactions (DDIs) and domain-motif interactions (DMIs) were inferred. To facilitate the reliability assessment of predicted PPIs, the source species of interolog templates, GO annotations, subcellular localizations and gene expression similarities are also provided. JavaScript packages were employed to visualize structures of protein complexes, protein interaction sites and protein interaction networks. We also developed an online tool for homology modelling and protein interaction site annotation of protein complexes. All data contained in PlaPPISite are also freely available on the Download page.Conclusion: PlaPPISite provides the plant research community with an easy-to-use and comprehensive data resource for the search and analysis of protein interaction details from the 13 important plant species.

1 August 2014 in Chinese Journal of Chemical Engineering
Verified
Journal Article
Closed access
WJWei Jiang
Wei Jiang
ZWZhiqiang Wen
Zhiqiang Wen
MWMianbin Wu
Mianbin Wu
HLHong Li
Hong Li
JYJun Yang
Jun Yang
PCPeilin Cen
Peilin Cen

8 December 2022 in Scientia Horticulturae
Verified
Journal Article
Closed access
CWCongcong Wang
Congcong Wang
JWJinshan Wu
Jinshan Wu
YTYanqiong Tang
Yanqiong Tang
YMYi Min
Yi Min
DWDan Wang
Dan Wang
ZLZhu Liu
Zhu Liu

27 September 2023 in Microbial Genomics
Verified
Journal Article
Open access
JMJiayue Ma
Jiayue Ma
HZHonghao Zhao
Honghao Zhao
SMShuangyi Mo
Shuangyi Mo
JLJuanjuan Li
Juanjuan Li
XMXiang Ma
Xiang Ma
ZLZhu Liu
Zhu Liu
Aeromonas veronii is an opportunistic pathogen that affects both fish and mammals, including humans, leading to bacteraemia, sepsis, meningitis and even death. The increasing virulence and drug resistance of A. veronii are of significant concern and pose a severe risk to public safety. The Type I restriction-modification (RM) system, which functions as a bacterial defence mechanism, can influence gene expression through DNA methylation. However, little research has been conducted to explore its origin, evolutionary path, and relationship to virulence and drug resistance in A. veronii . In this study, we analysed the pan-genome of 233 A . veronii strains, and the results indicated that it was 'open', meaning that A. veronii has acquired additional genes from other species. This suggested that A. veronii had the potential to adapt and evolve rapidly, which might have contributed to its drug resistance. One Type I methyltransferase (MTase) and two complete Type I RM systems were identified, namely AveC4I, AveC4II and AveC4III in A. veronii strain C4, respectively. Notably, AveC4I was exclusive to A. veronii C4. Phylogenetic analysis revealed that AveC4I was derived from horizontal gene transfer from Thiocystis violascens and exchanged genes with the human pathogen Comamonas kerstersii . Single molecule real-time sequencing was applied to identify the motif methylated by AveC4I, which was unique and not recognized by any reported MTases in the REBASE database. We also annotated the functions and pathways of the genes containing the motif, revealing that AveC4I may control drug resistance in A. veronii C4. Our findings provide new insight on the mechanisms underlying drug resistance in pathogenic bacteria. By identifying the specific genes and pathways affected by AveC4I, this study may aid in the development of new therapeutic approaches to combat A. veronii infections.

1 July 2019 in Microbial Pathogenesis
Verified
Journal Article
Closed access
LZLin Zhang
Lin Zhang
WYWenjing Yu
Wenjing Yu
YTYanqiong Tang
Yanqiong Tang
HLHong Li
Hong Li
XMXiang Ma
Xiang Ma
ZLZhu Liu
Zhu Liu