Multi-omics analysis of periodontal pocket microbial communities pre- and posttreatment

Katy J. Califf, Karen Schwarzberg-Lipson, Neha Garg, Sean M. Gibbons, James G Caporaso, Jørgen Slots, Chloe Cohen, Pieter C. Dorrestein, Scott T. Kelley

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

Periodontitis is a polymicrobial infectious disease that causes breakdown of the periodontal ligament and alveolar bone. We employed a meta-omics approach that included microbial 16S rRNA amplicon sequencing, shotgun metagenomics, and tandem mass spectrometry to analyze sub- and supragingival biofilms in adults with chronic periodontitis pre- and posttreatment with 0.25% sodium hypochlorite. Microbial samples were collected with periodontal curettes from 3- to 12- mm-deep periodontal pockets at the baseline and at 2 weeks and 3 months. All data types showed high interpersonal variability, and there was a significant correlation between phylogenetic diversity and pocket depth at the baseline and a strong correlation (rho = 0.21; P = 0.008) between metabolite diversity and maximum pocket depth (MPD). Analysis of subgingival baseline samples (16S rRNA and shotgun metagenomics) found positive correlations between abundances of particular bacterial genera and MPD, including Porphyromonas, Treponema, Tannerella, and Desulfovibrio species and unknown taxon SHD-231. At 2 weeks posttreatment, we observed an almost complete turnover in the bacterial genera (16S rRNA) and species (shotgun metagenomics) correlated with MPD. Among the metabolites detected, the medians of the 20 most abundant metabolites were significantly correlated with MPD pre- and posttreatment. Finally, tests of periodontal biofilm community instability found markedly higher taxonomic instability in patients who did not improve posttreatment than in patients who did improve (UniFrac distances; t = -3.59; P = 0.002). Interestingly, the opposite pattern occurred in the metabolic profiles (Bray- Curtis; t = 2.42; P = 0.02). Our results suggested that multi-omics approaches, and metabolomics analysis in particular, could enhance treatment prediction and reveal patients most likely to improve posttreatment.

Original languageEnglish (US)
Article numbere00016
JournalmSystems
Volume2
Issue number3
DOIs
StatePublished - May 1 2017

Fingerprint

Periodontal Pocket
Metagenomics
Firearms
Metabolites
microbial communities
microbial community
pretreatment
Biofilms
Biofilm
Porphyromonas
Baseline
Desulfovibrio
metabolite
Treponema
ribosomal RNA
Sodium Hypochlorite
Chronic Periodontitis
Periodontal Ligament
metabolites
Metabolomics

Keywords

  • 16S rRNA
  • Diagnostics
  • Metabolome
  • Microbiome
  • Molecular networking
  • Periodontal disease
  • Periodontitis
  • Shotgun metagenomics

ASJC Scopus subject areas

  • Molecular Biology
  • Physiology
  • Genetics
  • Biochemistry
  • Modeling and Simulation
  • Computer Science Applications
  • Ecology, Evolution, Behavior and Systematics
  • Microbiology

Cite this

Califf, K. J., Schwarzberg-Lipson, K., Garg, N., Gibbons, S. M., Caporaso, J. G., Slots, J., ... Kelley, S. T. (2017). Multi-omics analysis of periodontal pocket microbial communities pre- and posttreatment. mSystems, 2(3), [e00016]. https://doi.org/10.1128/mSystems.00016-17

Multi-omics analysis of periodontal pocket microbial communities pre- and posttreatment. / Califf, Katy J.; Schwarzberg-Lipson, Karen; Garg, Neha; Gibbons, Sean M.; Caporaso, James G; Slots, Jørgen; Cohen, Chloe; Dorrestein, Pieter C.; Kelley, Scott T.

In: mSystems, Vol. 2, No. 3, e00016, 01.05.2017.

Research output: Contribution to journalArticle

Califf, KJ, Schwarzberg-Lipson, K, Garg, N, Gibbons, SM, Caporaso, JG, Slots, J, Cohen, C, Dorrestein, PC & Kelley, ST 2017, 'Multi-omics analysis of periodontal pocket microbial communities pre- and posttreatment', mSystems, vol. 2, no. 3, e00016. https://doi.org/10.1128/mSystems.00016-17
Califf, Katy J. ; Schwarzberg-Lipson, Karen ; Garg, Neha ; Gibbons, Sean M. ; Caporaso, James G ; Slots, Jørgen ; Cohen, Chloe ; Dorrestein, Pieter C. ; Kelley, Scott T. / Multi-omics analysis of periodontal pocket microbial communities pre- and posttreatment. In: mSystems. 2017 ; Vol. 2, No. 3.
@article{67e645e7de474db2b1c7f977f33691ed,
title = "Multi-omics analysis of periodontal pocket microbial communities pre- and posttreatment",
abstract = "Periodontitis is a polymicrobial infectious disease that causes breakdown of the periodontal ligament and alveolar bone. We employed a meta-omics approach that included microbial 16S rRNA amplicon sequencing, shotgun metagenomics, and tandem mass spectrometry to analyze sub- and supragingival biofilms in adults with chronic periodontitis pre- and posttreatment with 0.25{\%} sodium hypochlorite. Microbial samples were collected with periodontal curettes from 3- to 12- mm-deep periodontal pockets at the baseline and at 2 weeks and 3 months. All data types showed high interpersonal variability, and there was a significant correlation between phylogenetic diversity and pocket depth at the baseline and a strong correlation (rho = 0.21; P = 0.008) between metabolite diversity and maximum pocket depth (MPD). Analysis of subgingival baseline samples (16S rRNA and shotgun metagenomics) found positive correlations between abundances of particular bacterial genera and MPD, including Porphyromonas, Treponema, Tannerella, and Desulfovibrio species and unknown taxon SHD-231. At 2 weeks posttreatment, we observed an almost complete turnover in the bacterial genera (16S rRNA) and species (shotgun metagenomics) correlated with MPD. Among the metabolites detected, the medians of the 20 most abundant metabolites were significantly correlated with MPD pre- and posttreatment. Finally, tests of periodontal biofilm community instability found markedly higher taxonomic instability in patients who did not improve posttreatment than in patients who did improve (UniFrac distances; t = -3.59; P = 0.002). Interestingly, the opposite pattern occurred in the metabolic profiles (Bray- Curtis; t = 2.42; P = 0.02). Our results suggested that multi-omics approaches, and metabolomics analysis in particular, could enhance treatment prediction and reveal patients most likely to improve posttreatment.",
keywords = "16S rRNA, Diagnostics, Metabolome, Microbiome, Molecular networking, Periodontal disease, Periodontitis, Shotgun metagenomics",
author = "Califf, {Katy J.} and Karen Schwarzberg-Lipson and Neha Garg and Gibbons, {Sean M.} and Caporaso, {James G} and J{\o}rgen Slots and Chloe Cohen and Dorrestein, {Pieter C.} and Kelley, {Scott T.}",
year = "2017",
month = "5",
day = "1",
doi = "10.1128/mSystems.00016-17",
language = "English (US)",
volume = "2",
journal = "mSystems",
issn = "2379-5077",
publisher = "American Society for Microbiology",
number = "3",

}

TY - JOUR

T1 - Multi-omics analysis of periodontal pocket microbial communities pre- and posttreatment

AU - Califf, Katy J.

AU - Schwarzberg-Lipson, Karen

AU - Garg, Neha

AU - Gibbons, Sean M.

AU - Caporaso, James G

AU - Slots, Jørgen

AU - Cohen, Chloe

AU - Dorrestein, Pieter C.

AU - Kelley, Scott T.

PY - 2017/5/1

Y1 - 2017/5/1

N2 - Periodontitis is a polymicrobial infectious disease that causes breakdown of the periodontal ligament and alveolar bone. We employed a meta-omics approach that included microbial 16S rRNA amplicon sequencing, shotgun metagenomics, and tandem mass spectrometry to analyze sub- and supragingival biofilms in adults with chronic periodontitis pre- and posttreatment with 0.25% sodium hypochlorite. Microbial samples were collected with periodontal curettes from 3- to 12- mm-deep periodontal pockets at the baseline and at 2 weeks and 3 months. All data types showed high interpersonal variability, and there was a significant correlation between phylogenetic diversity and pocket depth at the baseline and a strong correlation (rho = 0.21; P = 0.008) between metabolite diversity and maximum pocket depth (MPD). Analysis of subgingival baseline samples (16S rRNA and shotgun metagenomics) found positive correlations between abundances of particular bacterial genera and MPD, including Porphyromonas, Treponema, Tannerella, and Desulfovibrio species and unknown taxon SHD-231. At 2 weeks posttreatment, we observed an almost complete turnover in the bacterial genera (16S rRNA) and species (shotgun metagenomics) correlated with MPD. Among the metabolites detected, the medians of the 20 most abundant metabolites were significantly correlated with MPD pre- and posttreatment. Finally, tests of periodontal biofilm community instability found markedly higher taxonomic instability in patients who did not improve posttreatment than in patients who did improve (UniFrac distances; t = -3.59; P = 0.002). Interestingly, the opposite pattern occurred in the metabolic profiles (Bray- Curtis; t = 2.42; P = 0.02). Our results suggested that multi-omics approaches, and metabolomics analysis in particular, could enhance treatment prediction and reveal patients most likely to improve posttreatment.

AB - Periodontitis is a polymicrobial infectious disease that causes breakdown of the periodontal ligament and alveolar bone. We employed a meta-omics approach that included microbial 16S rRNA amplicon sequencing, shotgun metagenomics, and tandem mass spectrometry to analyze sub- and supragingival biofilms in adults with chronic periodontitis pre- and posttreatment with 0.25% sodium hypochlorite. Microbial samples were collected with periodontal curettes from 3- to 12- mm-deep periodontal pockets at the baseline and at 2 weeks and 3 months. All data types showed high interpersonal variability, and there was a significant correlation between phylogenetic diversity and pocket depth at the baseline and a strong correlation (rho = 0.21; P = 0.008) between metabolite diversity and maximum pocket depth (MPD). Analysis of subgingival baseline samples (16S rRNA and shotgun metagenomics) found positive correlations between abundances of particular bacterial genera and MPD, including Porphyromonas, Treponema, Tannerella, and Desulfovibrio species and unknown taxon SHD-231. At 2 weeks posttreatment, we observed an almost complete turnover in the bacterial genera (16S rRNA) and species (shotgun metagenomics) correlated with MPD. Among the metabolites detected, the medians of the 20 most abundant metabolites were significantly correlated with MPD pre- and posttreatment. Finally, tests of periodontal biofilm community instability found markedly higher taxonomic instability in patients who did not improve posttreatment than in patients who did improve (UniFrac distances; t = -3.59; P = 0.002). Interestingly, the opposite pattern occurred in the metabolic profiles (Bray- Curtis; t = 2.42; P = 0.02). Our results suggested that multi-omics approaches, and metabolomics analysis in particular, could enhance treatment prediction and reveal patients most likely to improve posttreatment.

KW - 16S rRNA

KW - Diagnostics

KW - Metabolome

KW - Microbiome

KW - Molecular networking

KW - Periodontal disease

KW - Periodontitis

KW - Shotgun metagenomics

UR - http://www.scopus.com/inward/record.url?scp=85041666146&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85041666146&partnerID=8YFLogxK

U2 - 10.1128/mSystems.00016-17

DO - 10.1128/mSystems.00016-17

M3 - Article

VL - 2

JO - mSystems

JF - mSystems

SN - 2379-5077

IS - 3

M1 - e00016

ER -