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Core of the saliva microbiome: an analysis of the MG-RAST data

BACKGROUND: Oral microbiota is considered as the second most complex in the human body and its dysbiosis can be responsible for oral diseases. Interactions between the microorganism communities and the host allow establishing the microbiological proles. Identifying the core microbiome is essential t...

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Autores principales: Oliveira, Simone G., Nishiyama, Rafaela R., Trigo, Claudio A. C., Mattos-Guaraldi, Ana Luiza, Dávila, Alberto M. R., Jardim, Rodrigo, Aguiar, Flavio H. B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8283749/
https://www.ncbi.nlm.nih.gov/pubmed/34271900
http://dx.doi.org/10.1186/s12903-021-01719-5
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author Oliveira, Simone G.
Nishiyama, Rafaela R.
Trigo, Claudio A. C.
Mattos-Guaraldi, Ana Luiza
Dávila, Alberto M. R.
Jardim, Rodrigo
Aguiar, Flavio H. B.
author_facet Oliveira, Simone G.
Nishiyama, Rafaela R.
Trigo, Claudio A. C.
Mattos-Guaraldi, Ana Luiza
Dávila, Alberto M. R.
Jardim, Rodrigo
Aguiar, Flavio H. B.
author_sort Oliveira, Simone G.
collection PubMed
description BACKGROUND: Oral microbiota is considered as the second most complex in the human body and its dysbiosis can be responsible for oral diseases. Interactions between the microorganism communities and the host allow establishing the microbiological proles. Identifying the core microbiome is essential to predicting diseases and changes in environmental behavior from microorganisms. METHODS: Projects containing the term “SALIVA”, deposited between 2014 and 2019 were recovered on the MG-RAST portal. Quality (Failed), taxonomic prediction (Unknown and Predicted), species richness (Rarefaction), and species diversity (Alpha) were analyzed according to sequencing approaches (Amplicon sequencing and Shotgun metagenomics). All data were checked for normality and homoscedasticity. Metagenomic projects were compared using the Mann–Whitney U test and Spearman's correlation. Microbiome cores were inferred by Principal Component Analysis. For all statistical tests, p < 0.05 was used. RESULTS: The study was performed with 3 projects, involving 245 Amplicon and 164 Shotgun metagenome datasets. All comparisons of variables, according to the type of sequencing, showed significant differences, except for the Predicted. In Shotgun metagenomics datasets the highest correlation was between Rarefaction and Failed (r =  − 0.78) and the lowest between Alpha and Unknown (r =  − 0.12). In Amplicon sequencing datasets, the variables Rarefaction and Unknown (r = 0.63) had the highest correlation and the lowest was between Alpha and Predicted (r =  − 0.03). Shotgun metagenomics datasets showed a greater number of genera than Amplicon. Propionibacterium, Lactobacillus, and Prevotella were the most representative genera in Amplicon sequencing. In Shotgun metagenomics, the most representative genera were Escherichia, Chitinophaga, and Acinetobacter. CONCLUSIONS: Core of the salivary microbiome and genera diversity are dependent on the sequencing approaches. Available data suggest that Shotgun metagenomics and Amplicon sequencing have similar sensitivities to detect the taxonomic level investigated, although Shotgun metagenomics allows a deeper analysis of the microorganism diversity. Microbiome studies must consider characteristics and limitations of the sequencing approaches. Were identified 20 genera in the core of saliva microbiome, regardless of the health condition of the host. Some bacteria of the core need further study to better understand their role in the oral cavity. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12903-021-01719-5.
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spelling pubmed-82837492021-07-19 Core of the saliva microbiome: an analysis of the MG-RAST data Oliveira, Simone G. Nishiyama, Rafaela R. Trigo, Claudio A. C. Mattos-Guaraldi, Ana Luiza Dávila, Alberto M. R. Jardim, Rodrigo Aguiar, Flavio H. B. BMC Oral Health Research BACKGROUND: Oral microbiota is considered as the second most complex in the human body and its dysbiosis can be responsible for oral diseases. Interactions between the microorganism communities and the host allow establishing the microbiological proles. Identifying the core microbiome is essential to predicting diseases and changes in environmental behavior from microorganisms. METHODS: Projects containing the term “SALIVA”, deposited between 2014 and 2019 were recovered on the MG-RAST portal. Quality (Failed), taxonomic prediction (Unknown and Predicted), species richness (Rarefaction), and species diversity (Alpha) were analyzed according to sequencing approaches (Amplicon sequencing and Shotgun metagenomics). All data were checked for normality and homoscedasticity. Metagenomic projects were compared using the Mann–Whitney U test and Spearman's correlation. Microbiome cores were inferred by Principal Component Analysis. For all statistical tests, p < 0.05 was used. RESULTS: The study was performed with 3 projects, involving 245 Amplicon and 164 Shotgun metagenome datasets. All comparisons of variables, according to the type of sequencing, showed significant differences, except for the Predicted. In Shotgun metagenomics datasets the highest correlation was between Rarefaction and Failed (r =  − 0.78) and the lowest between Alpha and Unknown (r =  − 0.12). In Amplicon sequencing datasets, the variables Rarefaction and Unknown (r = 0.63) had the highest correlation and the lowest was between Alpha and Predicted (r =  − 0.03). Shotgun metagenomics datasets showed a greater number of genera than Amplicon. Propionibacterium, Lactobacillus, and Prevotella were the most representative genera in Amplicon sequencing. In Shotgun metagenomics, the most representative genera were Escherichia, Chitinophaga, and Acinetobacter. CONCLUSIONS: Core of the salivary microbiome and genera diversity are dependent on the sequencing approaches. Available data suggest that Shotgun metagenomics and Amplicon sequencing have similar sensitivities to detect the taxonomic level investigated, although Shotgun metagenomics allows a deeper analysis of the microorganism diversity. Microbiome studies must consider characteristics and limitations of the sequencing approaches. Were identified 20 genera in the core of saliva microbiome, regardless of the health condition of the host. Some bacteria of the core need further study to better understand their role in the oral cavity. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12903-021-01719-5. BioMed Central 2021-07-16 /pmc/articles/PMC8283749/ /pubmed/34271900 http://dx.doi.org/10.1186/s12903-021-01719-5 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Oliveira, Simone G.
Nishiyama, Rafaela R.
Trigo, Claudio A. C.
Mattos-Guaraldi, Ana Luiza
Dávila, Alberto M. R.
Jardim, Rodrigo
Aguiar, Flavio H. B.
Core of the saliva microbiome: an analysis of the MG-RAST data
title Core of the saliva microbiome: an analysis of the MG-RAST data
title_full Core of the saliva microbiome: an analysis of the MG-RAST data
title_fullStr Core of the saliva microbiome: an analysis of the MG-RAST data
title_full_unstemmed Core of the saliva microbiome: an analysis of the MG-RAST data
title_short Core of the saliva microbiome: an analysis of the MG-RAST data
title_sort core of the saliva microbiome: an analysis of the mg-rast data
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8283749/
https://www.ncbi.nlm.nih.gov/pubmed/34271900
http://dx.doi.org/10.1186/s12903-021-01719-5
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