Evidence map›Paper›PMID 31999932›Full record

ArticleJournal of dental research2020

Modeling Normal and Dysbiotic Subgingival Microbiomes: Effect of Nutrients.

D Baraniya, M Naginyte, T Chen, J M Albandar, S M Chialastri, D A Devine, P D Marsh, N N Al-Hebshi

Open access · greenAbstract read
In one paragraph

Article in Journal of dental research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
3.4field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed, 33 citations in OpenAlex.

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  12. Optimization of conditions forFrontiers in microbiology · 2022
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 2 countries.

D BaraniyaOral Microbiome Research Laboratory, Department of Oral Health Sciences, Maurice H. Kornberg School of Dentistry, Temple University, Philadelphia, PA, USA.
M NaginyteDivision of Oral Biology, School of Dentistry, University of Leeds, Leeds, UK.
T ChenDepartment of Microbiology, Forsyth Institute, Cambridge, MA, USA.
J M AlbandarDepartment of Periodontology and Oral Implantology, Maurice H. Kornberg School of Dentistry, Temple University, Philadelphia, PA, USA.
S M ChialastriDepartment of Periodontology and Oral Implantology, Maurice H. Kornberg School of Dentistry, Temple University, Philadelphia, PA, USA.
D A DevineDivision of Oral Biology, School of Dentistry, University of Leeds, Leeds, UK.ORCID 0000-0002-8037-9254
P D MarshDivision of Oral Biology, School of Dentistry, University of Leeds, Leeds, UK.
N N Al-HebshiOral Microbiome Research Laboratory, Department of Oral Health Sciences, Maurice H. Kornberg School of Dentistry, Temple University, Philadelphia, PA, USA.ORCID 0000-0003-1841-9304
Temple University · USUniversity of Leeds · GB

Funding

In vitro reproducible model of subgingival microbiome for high throughput screening for microbiome modulatorsR03DE028379 · NIDCR · TEMPLE UNIV OF THE COMMONWEALTH · PI AL-HEBSHI, NEZAR · 2019 to 2020
$343k
NIDCR NIH HHS R03 DE028379
6 · The paper itself

Abstract

Screening for microbiome modulators requires availability of a high-throughput in vitro model that replicates subgingival dysbiosis and normobiosis, with a tool to measure microbial dysbiosis. Here, we tested various formulations to grow health- and periodontitis-associated subgingival microbiomes in parallel, and we describe a new subgingival dysbiosis index. Subgingival plaque samples pooled from 5 healthy subjects and, separately, 5 subjects with periodontitis were used to inoculate a Calgary Biofilm Device containing saliva-conditioned, hydroxyapatite-coated pegs. Microbiomes were grown for 7 d on either nutrient-rich media-including a modification of SHI medium, brain-heart infusion (BHI) supplemented with hemin and vitamin K, and a blend of SHI and BHI, each at 3 sucrose concentrations (0%, 0.05% and 0.1%)-or nutrient-limited media (saliva with 5%, 10%, or 20% inactivated human serum). The microbiomes were assessed for biomass, viability, and 16S rRNA profiles. In addition to richness and diversity, a dysbiosis index was calculated as the ratio of the sum of relative abundances of disease-associated species to that of health-associated species. The supplemented BHI and blend of SHI and BHI resulted in the highest biomass, whereas saliva-serum maximized viability. Distinct groups of bacteria were enriched in the different media. Regardless of medium type, the periodontitis-derived microbiomes showed higher species richness and alpha diversity and clustered with their inoculum separate from the health-derived microbiomes. Microbiomes grown in saliva-serum showed the highest species richness and the highest similarity to the clinical inocula in both health and disease. However, inclusion of serum reduced alpha diversity and increased dysbiosis in healthy microbiomes in a dose-dependent manner, mainly due to overenrichment of

Indexed as

DysbiosisMicrobiotaHumansNutrientsRNA, Ribosomal, 16SSalivaNutrientsRNA, Ribosomal, 16Sbiofilmdysbiosishigh-throughput nucleotide sequencingin vitro techniquesmicrobiotaperiodontitis

Identifiers

PMID31999932
PMCPMC7243421
OpenAlexW3001250034

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.