# Investigating the microbial basis of early childhood caries via metagenomics and metatranscriptomics analyses

> **NIH NIH R03** · UNIV OF NORTH CAROLINA CHAPEL HILL · 2020 · $149,335

## Abstract

Investigating the microbial basis of early childhood caries via metagenomics and
 metatranscriptomics analyses
Abstract
The increasing availability and scale of omics data have revolutionized our ability to understand
complex biological processes underlying health and disease. Such biologically-informed insights
are aligned with the notion of precision medicine and have the potential to improve diagnoses,
prevention and treatment. In the oral health domain, multiple omics data layers (e.g., genomics,
metagenomics, transcriptomics, metabolomics), intended to capture aspects of otherwise
unobservable biology, are increasingly being collected in oral health studies. However, methods
for powerful and informative integration of information gained from these multiple data layers
remains elusive. The focus of this proposal, early childhood caries (ECC), is the most common
chronic childhood disease. ECC is defined as dental decay among children under the age of 6—
it persists as a clinical and dental public health problem, and confers substantial and multi-level
human and economic impacts. The advent of precision oral health care, based upon a new,
microbially-informed understanding of ECC, is expected to shed light onto mechanistic aspects
of the disease processes and reveal new ways to prevent it. To this end, we will analyze
existing clinical (i.e., ECC case status) and matched metagenomics (whole genome sequencing
shotgun; WGS) and metatranscriptomics (RNA-seq.) data from supragingival plaque samples of
170 preschool-age children, mainly ages 3 and 4, enrolled in a community-based oral health
study in NC. The goal of the proposed study is to identify ECC-associated bacteria, bacterial
genes and pathways via metagenomics and metatranscriptomics analyses, conducted
separately and jointly. Aside from the unique characteristics (e.g., matched WGS and RNA-seq.
data from the same biofilm sample in each participant), quality and size of the dataset, the
proposal's novelty is amplified by the testing, development and dissemination of appropriate
statistical methods and optimized analytical pipelines. Seven models will be evaluated via
rigorous simulations, accounting for the handling of over-dispersion, zero-inflation, more than 2
phenotype groups and batch effects, and will be optimized prior to the real study data
application. Upon completion, we anticipate that the study will provide novel insights into the
microbial basis of ECC. The integrative data analysis framework will offer opportunities to
accommodate additional metabolomics data as they become available, to further increase the
potential for mechanistic insights.

## Key facts

- **NIH application ID:** 9978027
- **Project number:** 5R03DE028983-02
- **Recipient organization:** UNIV OF NORTH CAROLINA CHAPEL HILL
- **Principal Investigator:** Di Wu
- **Activity code:** R03 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $149,335
- **Award type:** 5
- **Project period:** 2019-08-01 → 2022-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9978027

## Citation

> US National Institutes of Health, RePORTER application 9978027, Investigating the microbial basis of early childhood caries via metagenomics and metatranscriptomics analyses (5R03DE028983-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9978027. Licensed CC0.

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