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Volume 11
Issue 8
10.3390/genes11080878
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Article

The Influences of Bioinformatics Tools and Reference Databases in Analyzing the Human Oral Microbial Community

by
Maria A. Sierra
1,
Qianhao Li
1,
Smruti Pushalkar
1,
Bidisha Paul
1,
Tito A. Sandoval
2,
Angela R. Kamer
1,
Patricia Corby
1,
Yuqi Guo
1,
Ryan Richard Ruff
3,
Alexander V. Alekseyenko
4,
Xin Li
1 and
Deepak Saxena
1,5,*
1
Department of Basic Science, New York University College of Dentistry, New York, NY 10010, USA
2
Department of Obstetrics and Gynecology, Weill Cornell Medicine, New York, NY 10065, USA
3
Department of Epidemiology & Health Promotion, New York University College of Dentistry, New York, NY 10010, USA
4
The Biomedical Informatics Center, Program for Human Microbiome Research, Department of Public Health Sciences, Department of Oral Health Sciences, Department of Healthcare Leadership and Management, Medical University of South Carolina, Charleston, SC 29425, USA
5
S. Arthur Localio Laboratory, Departments of Surgery New York University School of Medicine, New York, NY 10016, USA
*
Author to whom correspondence should be addressed.
Genes 2020, 11(8), 878; https://doi.org/10.3390/genes11080878
Received: 6 June 2020 / Revised: 11 July 2020 / Accepted: 29 July 2020 / Published: 3 August 2020
(This article belongs to the Collection Microbiome Analysis Techniques and Discovery)
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Abstract

There is currently no criterion to select appropriate bioinformatics tools and reference databases for analysis of 16S rRNA amplicon data in the human oral microbiome. Our study aims to determine the influence of multiple tools and reference databases on α-diversity measurements and β-diversity comparisons analyzing the human oral microbiome. We compared the results of taxonomical classification by Greengenes, the Human Oral Microbiome Database (HOMD), National Center for Biotechnology Information (NCBI) 16S, SILVA, and the Ribosomal Database Project (RDP) using Quantitative Insights Into Microbial Ecology (QIIME) and the Divisive Amplicon Denoising Algorithm (DADA2). There were 15 phyla present in all of the analyses, four phyla exclusive to certain databases, and different numbers of genera were identified in each database. Common genera found in the oral microbiome, such as Veillonella, Rothia, and Prevotella, are annotated by all databases; however, less common genera, such as Bulleidia and Paludibacter, are only annotated by large databases, such as Greengenes. Our results indicate that using different reference databases in 16S rRNA amplicon data analysis could lead to different taxonomic compositions, especially at genus level. There are a variety of databases available, but there are no defined criteria for data curation and validation of annotations, which can affect the accuracy and reproducibility of results, making it difficult to compare data across studies. View Full-Text
Keywords: 16S rRNA; databases; Greengenes; HOMD; NCBI; SILVA; RDP; QIIME; DADA2 16S rRNA; databases; Greengenes; HOMD; NCBI; SILVA; RDP; QIIME; DADA2
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MDPI and ACS Style

Sierra, M.A.; Li, Q.; Pushalkar, S.; Paul, B.; Sandoval, T.A.; Kamer, A.R.; Corby, P.; Guo, Y.; Ruff, R.R.; Alekseyenko, A.V.; Li, X.; Saxena, D. The Influences of Bioinformatics Tools and Reference Databases in Analyzing the Human Oral Microbial Community. Genes 2020, 11, 878. https://doi.org/10.3390/genes11080878

AMA Style

Sierra MA, Li Q, Pushalkar S, Paul B, Sandoval TA, Kamer AR, Corby P, Guo Y, Ruff RR, Alekseyenko AV, Li X, Saxena D. The Influences of Bioinformatics Tools and Reference Databases in Analyzing the Human Oral Microbial Community. Genes. 2020; 11(8):878. https://doi.org/10.3390/genes11080878

Chicago/Turabian Style

Sierra, Maria A., Qianhao Li, Smruti Pushalkar, Bidisha Paul, Tito A. Sandoval, Angela R. Kamer, Patricia Corby, Yuqi Guo, Ryan R. Ruff, Alexander V. Alekseyenko, Xin Li, and Deepak Saxena. 2020. "The Influences of Bioinformatics Tools and Reference Databases in Analyzing the Human Oral Microbial Community" Genes 11, no. 8: 878. https://doi.org/10.3390/genes11080878

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