Journal of Prevention and Treatment for Stomatological Diseases ›› 2021, Vol. 29 ›› Issue (3): 157-165.doi: 10.12016/j.issn.2096-1456.2021.03.003

• Basic Study • Previous Articles     Next Articles

High-throughput sequencing analysis of the microbiota of subgingival plaque in patients with periodontitis

YANG Wanjuan(),XU Jie()   

  1. Department of Periodontics, Stomatological Hospital of Kunming Medical University, Kunming 650106, China
  • Received:2020-04-24 Revised:2020-05-30 Online:2021-03-20 Published:2021-01-12
  • Contact: Jie XU E-mail:2809688235@qq.com;14799731@qq.com
  • Supported by:
    Science and Technology Planning Project of Yunnan Science and Technology Department(2018FE001[-261]);Health Science and Technology Project of Yunnan Province(2017NS267)

Abstract:

Objective To detect the composition of the subgingival microbiota in generalized aggressive periodontitis (GAgP) and severe chronic periodontitis (SCP) patients tested by high-throughput sequencing (HTS) technologies, analyze its diversity and function by using bioinformatics, and observe changes in the subgingival microbiota before and after periodontal initial therapy. Methods Eleven patients with GAgP and 14 patients with SCP who visited the Department of Periodontics in Stomatological Hospital of Kunming Medical University from September 2018 to May 2019 were recruited, and subgingival plaque samples were collected at baseline and 6 weeks after initial therapy. Then, the genomic DNA was distracted and sequenced by the Illumina MiSeq high-throughput sequencing platform. QIIME (quantitative insights in microbial ecology), Mothur, SPSS and other software were used to analyze community information. LEfSe difference analysis (linear discriminant analysis effect size), network analysis, and the KEGG PATHWAY database (https://www.kegg.jp/kegg/pathway.html) were used to predict community function. Results At baseline, the dominant microbiota of GAgP and SCP patients were similar, including Bacteroidetes, Porphyromonas and Porphyromonas endodontalis. Six weeks after initial therapy, as the periodontal pocket became shallower, the variation trend of the microbiota of GAgP and SCP patients was similar. The relative abundance of gram-negative bacteria, such as Bacteroidetes, Porphyromonas and Porphyromonas endodontalis, decreased, while the relative abundance of gram-positive bacteria, such as Proteobacteria, Actinomyces and Rothia aeria, increased. Actinobacteria were significantly increased biomarkers of the subgingival microbiota in GAgP after treatment. Streptococcus is an important genus that connects the microbiota related to periodontitis and the microbiota related to periodontal health. Community function prediction result showed that initial treatment can reduce the functions of amino acid metabolism, methane metabolism, and peptidase in GAgP and SCP patients. Conclusion The subgingival microbiota of GAgP and SCP patients are similar. Streptococcus, as an early colonizer, may play an important role in promoting plaque biofilm formation and maturation in the process of subgingival flora from health to imbalance. Initial therapy can change the composition and structure of the subgingival microbiota, reduce community diversity, and reduce the functions of amino acid metabolism, methane metabolism, and peptidase in GAgP and SCP patients.

Key words: generalized aggressive periodontitis, severe chronic periodontitis, subgingival plaque, subgingival microbiota, periodontal initial therapy, high-throughput sequencing, community diversity, community function prediction

CLC Number: 

  • R781.4

Figure 1

Histogram of relative abundance of dominant bacteria in each group at different classification levels a: phylum; b: genus; c: species; GAgP: generalized aggressive periodontitis; SCP: severe chronic periodontitis; QA: GAgP baseline; MA: SCP baseline; QB: GAgP after treatment; MB: SCP after treatment"

Figure 2

Relative abundance heatmap in genus level in GAgP group and SCP group before and after treatment The color represents the relative abundance value, the redder the color is, the higher the relative abundance is, the bluer the color is, the lower the relative abundance is; GAgP: generalized aggressive periodontitis; SCP: severe chronic periodontitis; QA: GAgP baseline; MA: SCP baseline; QB: GAgP after treatment; MB: SCP after treatment"

Table 1

The α diversity index of GAgP and SCP at baseline"

GAgP SCP t P
Shannon index 5.69 ± 0.46 5.67 ± 0.46 0.080 0.937
Simpson index 0.94 ± 0.02 0.94 ± 0.25 0.280 0.782

Table 2

The α diversity index of GAgP and SCP before and after initial therapy"

α diversity index Shannon index Simpson index
GAgP SCP GAgP SCP
Baseline 5.69 ± 0.46 5.67 ± 0.46 0.94 ± 0.02 0.94 ± 0.25
6th week after initial therapy 5.07 ± 0.76 5.32 ± 0.44 0.91 ± 0.05 0.93 ± 0.22
t 2.146 2.356 1.883 1.088
P 0.057 0.035 0.089 0.296

Figure 3

Rarefaction curve a: shannon index curve; b: simpson index curve; with the increase of sequencing depth, when the sequence number is more than 50 000, it indicates that the sequencing quantity is enough to cover all strains"

Figure 4

PCoA figure of the microbiota of subgingival plaque in each group before and after treatment a: PC1 vs. PC2 plot; b: PC3 vs. PC2 plot; c: PC1 vs. PC3 plot; GAgP: generalized aggressive periodontitis; SCP: severe chronic periodontitis; QA: GAgP baseline; MA: SCP baseline; QB: GAgP after treatment; MB: SCP after treatment; PC: principal coordinates; PCoA: principal coordinates analysis."

Figure 5

LEfSe analysis of the changes of subgingival microbiota in GAgP group before and after treatment In LEfSe, non parametric factorial Kruskal Wallis sum rank test was used to count the groups with significant difference in abundance, and then LDA was used to estimate the impact of species richness on the difference effect, but the effect of QA species richness on the difference effect cannot be calculated; a-b: phylum; c-d: class; e-f: order; GAgP: generalized aggressive periodontitis; SCP: severe chronic periodontitis; LEfSe: linear discriminant analysis effect size; LDA: linear discriminant analysis; QA: GAgP baseline; QB: GAgP after treatment"

Figure 6

Network analysis of genus level correlation"

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