Wenjie Hu

Prof. Wenjie Hu


Research Focus & Metrics

Academic Career Length

19Years (2008-Present)

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

Representative Publications

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1 May 2018 in Frontiers in Cellular and Infection Microbiology
Verified
Journal Article
Open access
PDF file
MSMeng Shi
Meng Shi
YWYiping Wei
Yiping Wei
WHWenjie Hu
Wenjie Hu
Yong NieYong Nie
Yong Nie
XWXiaolei Wu
Xiaolei Wu
RLRuifang Lu
Ruifang Lu
Periodontitis is a kind of infectious disease initiated by colonization of subgingival periodontal pathogens, which cause destruction of tooth-supporting tissues, and is a predominant threat to oral health as the most common cause of loss of teeth. The aim of this pilot study was to characterize the subgingival bacterial biodiversity of periodontal pockets with different probing depths in patients with different forms of periodontitis. Twenty-one subgingival plaque samples were collected from three patients with chronic periodontitis (ChP), three patients with aggressive periodontitis (AgP) and three periodontally healthy subjects (PH). Each patient with periodontitis was sampled at three sites, at different probing depths (PDs, one each at 4 mm, 5–6 mm, and ≥ 7 mm). Using 16S rRNA gene high-throughput sequencing and bioinformatic analysis, we found that subgingival communities in health and periodontitis samples largely differed. Meanwhile, Acholeplasma, Fretibacterium, Porphyromonas, Peptococcus, Treponema_2, Defluviitaleaceae_UCG_011, Filifactor, and Mycoplasma increased with the deepening of the pockets in ChP, whilst only Corynebacterium was negatively associated with PD. In AgP, Corynebacterium and Klebsiella were positively associated with PD, while Serratia, Pseudoramibacter, Defluviitaleaceae_UCG_011, and Desulfobulbus were negatively associated with PD. And among these two groups, Corynebacterium shifted differently. Moreover, in subgingival plaque, the unweighted UniFrac distances between samples from pockets with different PD in the same patients were significantly lower than those from pockets within the same PD category from different patients. This study demonstrated the shift of the subgingival microbiome in individual teeth sites during disease development. Within the limitation of the relative small sample size, this pilot study shed new light on the dynamic relationship between the extent of periodontal destruction and the subgingival microbiome.

11 March 2019 in Frontiers in Cellular and Infection Microbiology
Verified
Journal Article
Open access
PDF file
YWYiping Wei
Yiping Wei
MSMeng Shi
Meng Shi
MZMin Zhen
Min Zhen
CWCui Wang
Cui Wang
WHWenjie Hu
Wenjie Hu
XWXiaolei Wu
Xiaolei Wu
Periodontal microorganisms not only colonize subgingival pockets, but also are detected on various mucous membranes in patients with periodontitis. The object of this pilot study was, using the next-generation sequencing of 16S RNA gene, to characterize the microbiota in two oral habitats (buccal mucosas and subgingival pockets) in patients with different forms of periodontitis. Thirty-two buccal swab samples and 113 subgingival samples were obtained from eleven subjects with chronic periodontitis (ChP), twelve subjects with aggressive periodontitis (AgP), and nine periodontally healthy individuals (HP). Using Miseq Sequencing of 16S rRNA gene, we found that the subgingival and buccal mucosa microbiome of ChP and AgP patients both differed from HP. Meanwhile, Veillonella, Treponema, Filifactor, Fretibacterium, Peptostreptococcaceae_[XI][G-6], Peptostreptococcaceae_[XI][G-5], Bacteroidetes_[G-5], Bacteroidetes_[G-3], Peptostreptococcaceae_[XI][G-4], Peptostreptococcaceae_[XI][G-2] significantly increased both in buccal and subgingival plaque samples in periodontitis subjects (ChP and AgP) compared with HP. Moreover, the results based on the Unweighted UniFrac distance showed that buccal and subgingival plaque samples from the same individuals show higher community divergence than same habitats from different subject samples. This study demonstrated that the microbiome of buccal mucosa can be influenced by periodontitis. However, subgingival and buccal mucosa microbiome seem to be characterized by species-specific colonization patterns. This pilot study provides a glimpse at the changes of subgingival and buccal mucosa associated with periodontitis from a holistic view. Further studies should be taken to illuminate the interplay between these detected changes and periodontitis development.

29 January 2018 in Clinical Implant Dentistry and Related Research
Verified
Journal Article
Closed access
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LZLiping Zhao
Liping Zhao
TXTao Xu
Tao Xu
WHWenjie Hu
Wenjie Hu
KCKwok‐Hung Chung
Kwok‐Hung Chung

29 December 2017 in Journal of Esthetic and Restorative Dentistry
Verified
Journal Article
Closed access
PDF file
CWCui Wang
Cui Wang
WHWenjie Hu
Wenjie Hu
LLLing‐Zhi Liang
Ling‐Zhi Liang
YZYan‐Ling Zhang
Yan‐Ling Zhang
KCKwok‐Hung Chung
Kwok‐Hung Chung

11 January 2019 in Clinical Science
Verified
Journal Article
Closed access
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WHWenxue Huang
Wenxue Huang
YZYalin Zhan
Yalin Zhan
YZYunfei Zheng
Yunfei Zheng
YHYe Han
Ye Han
WHWenjie Hu
Wenjie Hu
JHJianXia Hou
JianXia Hou
Objective: Ferritin, an iron-binding protein, is ubiquitous and highly conserved; it plays a crucial role in inflammation, which is the main symptom of periodontitis. Full-length cDNA library analyses have demonstrated abundant expression of ferritin in human periodontal ligament. The aims of the present study were to explore how ferritin is regulated by local inflammation, and to investigate its functions and mechanisms of action in the process of periodontitis. Methods: Human gingival tissues were collected from periodontitis patients and healthy individuals. Experimental periodontitis was induced by ligature of second molars in mice. The expression of ferritin light polypeptide (FTL) and ferritin heavy polypeptide (FTH) were assessed by immunohistochemistry. Meanwhile, after stimulating human periodontal ligament cells (HPDLCs) with P. gingivalis-lipopolysaccharide (LPS), interleukin (IL)-6, and tumor necrosis factor-α (TNF-α), the expression of FTH and FTL were measured. Then, IL-6 and IL-8 were measured after incubation with different concentrations of apoferritin (iron-free ferritin) and several intracellular signaling pathway inhibitors, or after knockdown of the transferrin receptor. Results: Both FTH and FTL were substantially higher in inflamed periodontal tissues than in healthy tissues. The location of the elevated expression correlated well with the extent of inflammatory infiltration. Moreover, expression of FTH and FTL were enhanced after stimulation with P. gingivalis-LPS, IL-6, TNF-α. Apoferritin induced the production of IL-6 and IL-8 in a dose-dependent manner partly through binding to the transferrin receptor and activating ERK/P38 signaling pathways in HPDLCs. Conclusions: Ferritin is up-regulated by inflammation and exhibits cytokine-like activity in HPDLCs inducing a signaling cascade that promotes expression of pro-inflammatory cytokines associated with periodontitis.

30 November 2020 in Frontiers in Microbiology
Verified
Journal Article
Open access
PDF file
MSMeng Shi
Meng Shi
YWYiping Wei
Yiping Wei
YNYong Nie
Yong Nie
CWCui Wang
Cui Wang
FSFei Sun
Fei Sun
Xiao-lei WuXiao-lei Wu
Xiao-lei Wu
This study aimed to characterize the microbial community and metabolic profiles in generalized aggressive periodontitis (AgP) using 16S ribosomal RNA (rRNA) gene high-throughput sequencing and gas chromatography-mass spectrometry (GC-MS). A total of 146 subgingival plaque samples and 50 gingival crevicular fluid (GCF) samples were collected from 24 patients with AgP and 10 periodontally healthy subjects (PH). Striking differences were observed in subgingival microbiome and GCF metabolomics between patients with AgP and PH, but not between samples with different probing depths (PDs). Metabolomics analysis combined with enrichment analysis showed that periodontitis significantly altered the concentration of compounds associated with biosynthesis of amino acids (e.g., alanine, leucine, isoleucine, and valine), galactose metabolism (e.g., myo-inositol, galactose, glucose, and hexitol), and pyrimidine metabolism (e.g., uracil, uridine, beta alanine, and thymine). Correlation analysis showed that the genera with significant difference between AgP and PH were usually significantly correlated with more metabolites, such asAggregatibacter,Rothia,Peptostreptococcaceae_[XI][G-5], andBacteroidaceae_[G-1]. While glucose and oxoproline had the most significant correlations with microorganisms. Our results revealed distinct microbial communities and metabolic profiles between AgP and PH. The significant correlation between microbial taxa and metabolites suggested the possible mechanisms for periodontitis. Our results also provided effective approaches for detecting periodontal disease and managing periodontitis.