Cited by 24Oral microbiology and periodontitis researchDental Health and Care UtilizationGut microbiota and health

The DOI matches its Crossref record; 65 of the 65 references it cites were found in a registry or an index; 19 of the 62 sources its claims cite were checked for support.

Saliva microbiome alterations in dental fluorosis population

Open access

Abstract

Background We aimed to explore saliva microbiome alterations in dental fluorosis population.Methods The prevalence of dental fluorosis was examined in 957 college students. Dean’s fluorosis index was used to evaluate the dental fluorosis status. Changes in the composition of the salivary microbiome were assessed in a subset of these patients (100 healthy controls, 100 dental fluorosis patients).Results Dental fluorosis affected 47% of the student sample, and incidence was unrelated to gender. Compared with healthy controls, the microbiota of patients with dental fluorosis exhibited increased diversity, with increased abundance of Treponema lecithinolyticum, Vibrio metschnikovii, Cupriavidus pauculus, Pseudomonas, Pseudomonadaceae, Pseudomonadales, and decreased abundance of Streptococcus mutans, Streptococcus sanguinis, Gemella, and Staphylococcales. Function analyses showed increases in arginine biosynthesis in patients affected by dental fluorosis, together with reductions in amino sugar and nucleotide sugar metabolism, fructose and mannose metabolism, and starch and sucrose metabolism.Conclusions These results suggest that there are striking differences in salivary microbiome between healthy controls and dental fluorosis patients. Dental fluorosis may contribute to periodontitis and systemic lung diseases. There is a need for cohort studies to determine whether altering the salivary microbiota in dental fluorosis patients can alter the development of oral or systemic diseases.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

Salivary microbiome profiling in college students found dental fluorosis prevalence of 47% and distinct oral microbial composition in affected individuals, including higher richness and altered taxa. The authors suggest these changes may relate to periodontitis and systemic lung disease risk, but cohort studies are needed.

Key findings

  • Among 957 college students, dental fluorosis prevalence was 47% (n = 450), with no significant difference by gender (P = 0.114) or severity by gender (P = 0.976).
  • The dental fluorosis group had increased salivary α-diversity richness (Chao1, P < 0.001) but no significant evenness difference (Pielou_e, P = 0.364); β-diversity differed significantly (Bray-Curtis, P = 0.001).
  • Increased taxa in dental fluorosis included Treponema lecithinolyticum, Vibrio metschnikovii, Cupriavidus pauculus, Pseudomonas, Pseudomonadaceae, and Pseudomonadales; decreased taxa included Streptococcus mutans (P = 0.004), Streptococcus sanguinis, Gemella, and Staphylococcales.
  • PICRUSt2 predicted increased arginine biosynthesis and reductions in amino sugar/nucleotide sugar metabolism, fructose/mannose metabolism, and starch/sucrose metabolism; >90% of functional genes were under-represented in the dental fluorosis group.

Methods

  • Cross-sectional study at Bengbu Medical College, China: 957 students screened for dental fluorosis using Dean’s fluorosis index; microbiome analyses used a subset of 100 healthy controls and 100 dental fluorosis patients (abstract), with Results/Discussion describing 199 samples (100 controls, 99 dental fluorosis).
  • Saliva samples underwent 16S rRNA V3–V4 sequencing; taxonomic classification used SILVA v138.1 and NCBI; analyses included Chao1, Pielou_e, NMDS on Bray-Curtis distances, Metastats, random forest with ROC curves, and PICRUSt2.
  • Statistics used SPSS 20.0 with Pearson chi-square, continuity correction, or Fisher’s exact test (P < 0.05); microbiome differential abundance used Metastats with corrected P < 0.05.

Limitations

  • Stated: only college students were recruited, potentially limiting accuracy and generalizability of dental fluorosis prevalence; the authors note the need for long-term cohort studies to understand mechanisms and disease incidence.
  • Evident: the cross-sectional design cannot establish whether salivary microbiome changes contribute to or result from dental fluorosis.
  • Evident: the text contains a sample-count inconsistency—the abstract states 100 dental fluorosis patients, while Results/Discussion describe 199 samples (100 controls, 99 dental fluorosis).

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1080/20002297.2023.2180927

Cites

65 of 65 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Figures

Figure 1. Study design.
Figure 1. Study design.CC BY · PubMed Central
Figure 2. Taxonomic profiles of the oral microbiota in dental fluorosis patients and healthy controls. (a) a Venn diagram corresponding to the ASV in these two groups. (b) α diversity indexes (Chao 1 for richness and Pielou_e for evenness). (c) NMDS analyses of the DF and HC groups based on Bray-Curtis distance values. *** represents p-value less than 0.001.
Figure 2. Taxonomic profiles of the oral microbiota in dental fluorosis patients and healthy controls. (a) a Venn diagram corresponding to the ASV in these two groups. (b) α diversity indexes (Chao 1 for richness and Pielou_e for evenness). (c) NMDS analyses of the DF and HC groups based on Bray-Curtis distance values. *** represents p-value less than 0.001.CC BY · PubMed Central
Figure 3. Oral microbiome changes in the 10 most dominant taxa at each level in dental fluorosis population. Metastats was used to assess differences in taxonomic composition. * represents corrected p-value less than 0.05. ** represents corrected p-value less than 0.01.
Figure 3. Oral microbiome changes in the 10 most dominant taxa at each level in dental fluorosis population. Metastats was used to assess differences in taxonomic composition. * represents corrected p-value less than 0.05. ** represents corrected p-value less than 0.01.CC BY · PubMed Central
Figure 4. Random forest model analysis. Classification performance of the top three taxa generated by random forest model were assessed by ROC curves. Taxa with AUC values below 0.9 for phylum and class are not displayed.
Figure 4. Random forest model analysis. Classification performance of the top three taxa generated by random forest model were assessed by ROC curves. Taxa with AUC values below 0.9 for phylum and class are not displayed.CC BY · PubMed Central
Figure 5. Taxonomic profiles of the oral microbiota in subgroup. (a and c) α diversity indexes (Chao 1 for richness and Pielou_e for evenness). (b and d) NMDS analyses of these groups based on Bray-Curtis distance values.
Figure 5. Taxonomic profiles of the oral microbiota in subgroup. (a and c) α diversity indexes (Chao 1 for richness and Pielou_e for evenness). (b and d) NMDS analyses of these groups based on Bray-Curtis distance values.CC BY · PubMed Central
Figure 6. Functional genes identified through PICRUSt 2 analysis. Genes related to taxa with abundance greater than 0.001 and with p-values less than 0.01 in either group are shown.
Figure 6. Functional genes identified through PICRUSt 2 analysis. Genes related to taxa with abundance greater than 0.001 and with p-values less than 0.01 in either group are shown.CC BY · PubMed Central

Verification

Claims the paper makes

25 Own result · 18 Not checked yet · 11 Own interpretation · 8 No full text of the sources · 4 Partly supported · 3 Own method · 2 Supported · 2 No basis given · 1 Supported so far · accuracy not yet measured

Verify all 25 references — free account

Show all 42 claims

  • Probably not a substantial claim. 25
  • It may state two separate claims as one. 15
  • The quote only partly states this claim. 1
32 of 32
  • The paper relies on this without support.

    PICRUSt2-predicted functional profiles accurately represent the actual functional capabilities of the salivary microbiome.

    “PICRUSt 2 algorithm was used to assess the predicted biological functions of the microbiome in DF and HC group participants, providing a comprehensive overview of differences in salivary ecological characteristics in these groups.”
  • The paper relies on this without support.

    The V3-V4 region of 16S rRNA provides sufficient taxonomic resolution to identify bacterial species and genera.

    “Thus, we chose the V3-V4 hypervariable 16S rRNA gene sequences for analysis in the current study.”
    “At the species level, Streptococcus mutans, an important cariogenic bacterium, was present at significantly lower abundance in the DF group relative to the HC group (P = 0.004).”
  • The paper relies on this without support.

    The functional genes K07024, K00688, and K00975 are involved in starch and sucrose metabolism.

    “K07024 (SPP, sucrose-6-phosphatase), K00688 (glgP, glycogen phosphorylase), K00975 (glgC, glucose-1-phosphate adenylyltransferase) are involved in starch and sucrose metabolism.”
  • The paper relies on this without support.

    The functional genes K02794, K02795, and K02796 are involved in fructose and mannose metabolism and amino sugar and nucleotide sugar metabolism.

    “K02794 (manX, mannose PTS system EIIAB component), K02795 (manY, mannose PTS system EIIC component), and K02796 (manZ, mannose PTS system EIID component) are involved in fructose and mannose metabolism and amino sugar and nucleotide sugar metabolism.”
  • The paper relies on this without support.

    The argR and ahrC genes (K03402) are transcriptional regulators of arginine metabolism.

    “argR and ahrC (K03402; argR, ahrC; transcriptional regulator of arginine metabolism)”
5 of 5

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

1 of 1

Citations

Cites

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Metadata

Authors
Liu, S., Song, Q., Zhang, C., Li, M., Li, Z., Liu, Y., Xu, L., Xie, X., Zhao, L., Zhang, R., Wang, Q., Zeng, G., Zhang, Y., & Zhang, K.
Affiliations
  • Bengbu Medical College (CN)
  • Department of Stomatology, Huaiyuan county people’s Hospital, Bengbu, China
  • First Affiliated Hospital of Bengbu Medical College (CN)
  • Department of Stomatology, The First Affiliated Hospital of Bengbu Medical College, Bengbu, China
Corresponding author
Zhang, Kai
Venue
Journal of Oral Microbiology
Published
2023-02-20
Volume
15
Issue
1
Pages
2180927-2180927
ISSN
2000-2297 (ISSN-L)
OpenAlex
W4321458033
Cited by
24
References
65
Citations by year
2026: 7 · 2025: 8 · 2024: 4 · 2023: 5
FWCI
4.26
Type
journal article
Language
en
Open access
Locations
  • Journal of Oral Microbiology (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • National Natural Science Foundation of China (32000386)
  • the First Affiliated Hospital of Bengbu Medical College Science Fund for Outstanding Young Scholars (2019byyfyyq07)
  • the University Synergy Innovation Program of Anhui Province, China (GXXT-2021-056)
  • Key project of natural science of Bengbu Medical College (2020byzd058)
Topics
  • Health Sciences › Dentistry › Periodontics › Oral microbiology and periodontitis research
  • Health Sciences › Dentistry › General Dentistry › Dental Health and Care Utilization
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
Keywords
dental fluorosis, salivary microbiome, oral microbiota, microbial diversity, Dean's fluorosis index, Vibrio metschnikovii, Pseudomonas, Streptococcus mutans, arginine biosynthesis, carbohydrate metabolism, periodontitis, university students

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