Paper - Review

DOI: 10.1128/mSystems.00016-17

Abstract

Periodontitits
→ is a poly-microbial infectious diseases
← causes breakdown of 1⃣ the periodontal ligament 2⃣ alveolar bone

❗: Employed → a meta-omics approach
← that included 1⃣ microbial 16S rRNA amplicon sequencing 2⃣ shotgun metagenomics 3⃣ tandem mass spectrometry
→ to analyze 1⃣ sub- 2⃣ supra-gingival biofilms
← in adults with chronic periodontitis
← 1⃣ pre- 2⃣ post-treatment with 0.25% (sodium hypochlorite)

Microbial samples
→ were collected ← in periodontal curettes
← from 3- to 12-mm-deep periodontal pockets
← 1⃣ at the baseline 2⃣ at 2 weeks 3⃣ 3 months

All data types
→ showed → high inter-personal variability

❗: a significant correlation
← between 1⃣ phylogenetic diversity 2⃣ pocket depth
❗: a strong correlation
← between 1⃣ metabolite diversity 2⃣ maximum pocket depth

Analysis of sub-gingival baseline samples
→ found → positive correlations
← between 1⃣ abundances of particular bacterial genera 2⃣ MPD

Observed → an almost complete turnover
← in 1⃣ the bacterial genera 2⃣ species ← correlated with MPD
← at 2 weeks post-treatment

Medians ← of the 20 most abundant metabolites
→ were significantly correlated ← with 1⃣ MPD pre- 2⃣ post-treatment

Test of (periodontal biofilm community instability)
→ found → markedly higher taxonomic instability
← in patients who did NOT ❌ improve post-treatment

The opposite pattern
→ occurred ← in the metabolic profiles

1⃣ Multi-omics approaches 2⃣ metabolomics analysis
→ could enhance treatment prediction
→ reveal patients → most likely to improve post-treatment

Importance

Periodontal disease
→ affects the majority of adults worldwide
→ has been linked → to numerous systemic diseases

The reasons
→ for the substantial differences ← among periodontitis patients
← in 1⃣ disease incidence 2⃣ progressivity 3⃣ response → to treatment
→ remain poorly understood

❗: Deep sequencing of (oral bacterial communities)
→ has greatly expanded → our comprehension of (the microbial diversity ← of periodontal disease)
→ identified associations ← with 1⃣ healthy 2⃣ disease states
❓: predicting treatment outcomes → remains elusive

Combining multiple omics approaches
→ enhances the ability → to differentiate among disease states
→ determine differential effects of treatment
← with the addition of metabolomic information

❗: these approches → provide new tools
→ for investigating the ecological dynamics
← underlying the progressive periodontal disease process
∵ multi-omics analysis of biofilm community instability

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