Studying Oral Bacteria in Periodontal Disease Using Advanced DNA Sequencing and the DADA2 Pipeline
Session Number
3
Advisor(s)
Dr. Guy Adami, University of Illinois Chicago
Location
A147
Discipline
Medical and Health Sciences
Start Date
15-4-2026 2:15 PM
End Date
15-4-2026 3:00 PM
Abstract
Periodontal disease, commonly known as gum disease, is caused by an imbalance of bacteria living in the mouth. To better understand which bacteria are present in patients with periodontal disease compared to healthy individuals, we analyzed clinical oral samples using a DNA sequencing technology called PacBio Kinnex long-read sequencing. This method allows us to read the full length of the 16S rRNA gene, which works like a bacterial "fingerprint" to identify different species. Until recently, this type of sequencing was limited to short 100–500 base sections of the gene due to technological constraints. Full length sequencing of the ~1,500 bases allows greater accuracy in species identification, though computational pipelines are still being optimized. Raw sequencing data was processed using the DADA2 software pipeline to filter low-quality reads, remove errors, and identify unique bacterial sequences. Bacteria were then identified by comparing our sequences against the SILVA database, a large library of known bacterial rRNA genes. Our analysis identified key oral bacteria including Streptococcus, Rothia, Neisseria, and Haemophilus. This study provides a reliable method for understanding how bacterial communities in the mouth differ between healthy individuals and those with disease, contributing to ongoing research at the University of Illinois Chicago.
Studying Oral Bacteria in Periodontal Disease Using Advanced DNA Sequencing and the DADA2 Pipeline
A147
Periodontal disease, commonly known as gum disease, is caused by an imbalance of bacteria living in the mouth. To better understand which bacteria are present in patients with periodontal disease compared to healthy individuals, we analyzed clinical oral samples using a DNA sequencing technology called PacBio Kinnex long-read sequencing. This method allows us to read the full length of the 16S rRNA gene, which works like a bacterial "fingerprint" to identify different species. Until recently, this type of sequencing was limited to short 100–500 base sections of the gene due to technological constraints. Full length sequencing of the ~1,500 bases allows greater accuracy in species identification, though computational pipelines are still being optimized. Raw sequencing data was processed using the DADA2 software pipeline to filter low-quality reads, remove errors, and identify unique bacterial sequences. Bacteria were then identified by comparing our sequences against the SILVA database, a large library of known bacterial rRNA genes. Our analysis identified key oral bacteria including Streptococcus, Rothia, Neisseria, and Haemophilus. This study provides a reliable method for understanding how bacterial communities in the mouth differ between healthy individuals and those with disease, contributing to ongoing research at the University of Illinois Chicago.