scholarly journals Importance of Interkingdom Interactions Among Oral Microbiome Towards Caries Development – A Review

2021 ◽  
Vol 5 (2) ◽  
pp. 27-35
Author(s):  
Kalpana Balakrishnan ◽  
Divya Sivanesan ◽  
Gaanappriya Mohan ◽  
Sachin Gunthe ◽  
Rama Verma
Keyword(s):  
Human Microbiome ◽  
Oral Microbiome ◽  
Systemic Diseases ◽  
Holistic View ◽  
Host System ◽  
Bacterial Diseases ◽  
Microbial Network ◽  
Health And Disease ◽  
Ecological Shifts ◽  
Candidate Phyla Radiation

The human microbiome plays a crucial role in health and disease conditions. These microbiomes constitute a structured, coordinated microbial network throughout the human body. The oral cavity harbors one of the extensively diverse bacteria in the human system. Although many studies emphasize bacteriome and its interaction with the host system, very little attention is given to candidate phyla radiation (CPR), fungal components, and its interkingdom interaction in the oral microecology even with advanced techniques. The interkingdom interactions among caries causing microbes trigger the pathogenesis of bacterial diseases and cause ecological shifts and affect the host system. Studying the complex relations among the diverse oral microbiome and its host, especially CPR phyla and fungi, would give a holistic view of the caries etiology. This review provides evidence on the interkingdom interaction that establishes a complex community that could help predict future oral and systemic diseases.

scholarly journals The oral microbiome

2017 ◽  
Vol 1 (4) ◽  
pp. 287-296 ◽  
Author(s):  
Liam P. Shaw ◽  
Andrew M. Smith ◽  
Adam P. Roberts
Keyword(s):  
Human Microbiome ◽  
Oral Microbiome ◽  
Core Microbiome ◽  
Individual Level ◽  
Host Interactions ◽  
Paradoxical Situation ◽  
Health And Disease ◽  
Stable Core ◽  
The Individual ◽  
Conserved Core

The human microbiome is receiving a great deal of attention as its role in health and disease becomes ever more apparent. The oral microbiome, perhaps due to the ease with which we can obtain samples, is arguably the most well-studied human microbiome to date. It is obvious, however, that we have only just begun to scratch the surface of the complex bacterial and bacterial–host interactions within this complex community. Here, we describe the factors which are known to influence the development of the seemingly globally conserved, core, oral microbiome and those which are likely to be responsible for the observed differences at the individual level. We discuss the paradoxical situation of maintaining a stable core microbiome which is at the same time incredibly resilient and adaptable to many different stresses encountered in the open environment of the oral cavity. Finally, we explore the interactions of the oral microbiome with the host and discuss the interactions underlying human health and disease.

scholarly journals Oral Microbiome and Host Health: Review on Current Advances in Genome-Wide Analysis

2021 ◽  
Vol 11 (9) ◽  
pp. 4050
Author(s):  
Young-Dan Cho ◽  
Kyoung-Hwa Kim ◽  
Yong-Moo Lee ◽  
Young Ku ◽  
Yang-Jo Seol
Keyword(s):  
Molecular Mechanisms ◽  
Close Association ◽  
Human Microbiome ◽  
Oral Microbiome ◽  
Systemic Diseases ◽  
Future Directions ◽  
Genome Wide Analysis ◽  
Host Interaction ◽  
Genome Wide ◽  
Special Environment

The oral microbiome is an important part of the human microbiome. The oral cavity has the second largest microbiota after the intestines, and its open structure creates a special environment. With the development of technology such as next-generation sequencing and bioinformatics, extensive in-depth microbiome studies have become possible. They can also be applied in the clinical field in terms of diagnosis and treatment. Many microbiome studies have been performed on oral and systemic diseases, showing a close association between the two. Understanding the oral microbiome and host interaction is expected to provide future directions to explore the functional and metabolic changes in diseases, and to uncover the molecular mechanisms for drug development and treatment that facilitate personalized medicine. The aim of this review was to provide comprehension regarding research trends in oral microbiome studies and establish the link between oral microbiomes and systemic diseases based on the latest technique of genome-wide analysis.

scholarly journals Metatranscriptome of the Oral Microbiome in Health and Disease

2018 ◽  
Vol 97 (5) ◽  
pp. 492-500 ◽  
Author(s):  
J. Solbiati ◽  
J. Frias-Lopez
Keyword(s):  
Oral Microbiome ◽  
Health And Disease

scholarly journals OTUs clustering should be avoided for defining oral microbiome

2021 ◽  
Author(s):  
Alba Regueira-Iglesias ◽  
Lara Vazquez-Gonzalez ◽  
Carlos Balsa-Castro ◽  
Triana Blanco-Pintos ◽  
Victor Manuel Arce ◽  
...  
Keyword(s):  
Microbial Diversity ◽  
Operational Taxonomic Unit ◽  
Oral Bacteria ◽  
Oral Microbiome ◽  
Rrna Gene ◽  
Oral Microbiota ◽  
High Coverage ◽  
Archaeal Species ◽  
Health And Disease ◽  
Similarity Relationships

This in silico investigation aimed to: 1) evaluate a set of primer pairs with high coverage, including those most commonly used in the literature, to find the different oral species with 16S rRNA gene amplicon similarity/identity (ASI) values ≥97%; and 2) identify oral species that may be erroneously clustered in the same operational taxonomic unit (OTU) and ascertain whether they belong to distinct genera or other higher taxonomic ranks. Thirty-nine primer pairs were employed to obtain amplicon sequence variants (ASVs) from the complete genomes of 186 bacterial and 135 archaeal species. For each primer, ASVs without mismatches were aligned using BLASTN and their similarity values were obtained. Finally, we selected ASVs from different species with an ASI value ≥97% that were covered 100% by the query sequences. For each primer, the percentage of species-level coverage with no ASI≥97% (SC-NASI≥97%) was calculated. Based on the SC-NASI≥97% values, the best primer pairs were OP_F053-KP_R020 for bacteria (65.05%), KP_F018-KP_R002 for archaea (51.11%), and OP_F114-KP_R031 for bacteria and archaea together (52.02%). Eighty percent of the oral-bacteria and oral-archaea species shared an ASI≥97% with at least one other taxa, including Campylobacter, Rothia, Streptococcus, and Tannerella, which played conflicting roles in the oral microbiota. Moreover, around a quarter and a third of these two-by-two similarity relationships were between species from different bacteria and archaea genera, respectively. Furthermore, even taxa from distinct families, orders, and classes could be grouped in the same cluster. Consequently, irrespective of the primer pair used, OTUs constructed with a 97% similarity provide an inaccurate description of oral-bacterial and oral-archaeal species, greatly affecting microbial diversity parameters. As a result, clustering by OTUs impacts the credibility of the associations between some oral species and certain health and disease conditions. This limits significantly the comparability of the microbial diversity findings reported in oral microbiome literature.

scholarly journals Health and disease imprinted in the time variability of the human microbiome

2015 ◽  
Author(s):  
Jose Manuel Marti ◽  
Daniel M Martinez ◽  
Manuel Pena ◽  
Cesar Gracia ◽  
Amparo Latorre ◽  
...  
Keyword(s):  
Temporal Variability ◽  
Scaling Law ◽  
Human Microbiome ◽  
Time Variability ◽  
Clinical Use ◽  
Gut Development ◽  
Research Activity ◽  
Health And Disease ◽  
Fluctuation Scaling ◽  
Universal Law

Human microbiota plays an important role in determining changes from health to disease. Increasing research activity is dedicated to understand its diversity and variability. We analyse 16S rRNA and whole genome sequencing (WGS) data from the gut microbiota of 97 individuals monitored in time. Temporal fluctuations in the microbiome reveal significant differences due to factors that affect the microbiota such as dietary changes, antibiotic intake, early gut development or disease. Here we show that a fluctuation scaling law describes the temporal variability of the system and that a noise-induced phase transition is central in the route to disease. The universal law distinguishes healthy from sick microbiota and quantitatively characterizes the path in the phase space, which opens up its potential clinical use and, more generally, other technological applications where microbiota plays an important role.

scholarly journals Preface to the human microbiome in urologic health and disease

2017 ◽  
Vol 5 ◽  
pp. 27-27 ◽  
Author(s):  
Daniel A. Shoskes ◽  
Jill A. Macoska
Keyword(s):  
Human Microbiome ◽  
Health And Disease

scholarly journals Microbial trend analysis for common dynamic trend, group comparison and classification in longitudinal microbiome study

2020 ◽  
Author(s):  
Chan Wang ◽  
Jiyuan Hu ◽  
Martin J. Blaser ◽  
Huilin Li
Keyword(s):  
Trend Analysis ◽  
Critical Role ◽  
Human Microbiome ◽  
Real Data ◽  
Microbial Dynamics ◽  
Individual Subject ◽  
Microbial Profiling ◽  
Health And Disease ◽  
Microbiome Data

AbstractMotivationThe human microbiome is inherently dynamic and its dynamic nature plays a critical role in maintaining health and driving disease. With an increasing number of longitudinal microbiome studies, scientists are eager to learn the comprehensive characterization of microbial dynamics and their implications to the health and disease-related phenotypes. However, due to the challenging structure of longitudinal microbiome data, few analytic methods are available to characterize the microbial dynamics over time.ResultsWe propose a microbial trend analysis (MTA) framework for the high-dimensional and phylogenetically-based longitudinal microbiome data. In particular, MTA can perform three tasks: 1) capture the common microbial dynamic trends for a group of subjects on the community level and identify the dominant taxa; 2) examine whether or not the microbial overall dynamic trends are significantly different in groups; 3) classify an individual subject based on its longitudinal microbial profiling. Our extensive simulations demonstrate that the proposed MTA framework is robust and powerful in hypothesis testing, taxon identification, and subject classification. Our real data analyses further illustrate the utility of MTA through a longitudinal study in mice.ConclusionsThe proposed MTA framework is an attractive and effective tool in investigating dynamic microbial pattern from longitudinal microbiome studies.

scholarly journals Composition of the Oral Microbiome in Patients with Coronary Artery Disease

2020 ◽  
Author(s):  
Thangam Menon ◽  
Supraja Kalyanaraman ◽  
Seethalakshmi Srinivasan
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Bacterial Flora ◽  
Human Microbiome ◽  
Oral Microbiome ◽  
Metagenomic Analysis ◽  
Control Group ◽  
Oral Microbiota ◽  
Normal Human ◽  
Artery Disease

Introduction: Distinct microbial communities reside in the oral cavity and the composition of the oral microbiota has important implications for human health and disease. Identification of bacterial flora of the microbiome is done by metagenomic analysis of 16S ribosomal RNA sequences. Aim: The aim of this study was to characterise the human microbiome in patients with Coronary Artery Disease (CAD) in comparison with the normal human microbiome. Materials and Methods: A pilot study was carried out in tertiary hospital, Chennai. Oral mouthwash samples collected from nine patients with CAD were selected, with one control group. They were studied by metagenomic analysis of V3-V4 region of 16SrRNA gene sequences.. Sequencing of the variable V3 and V4 regions was done using Illumina platform. Results: The six major phyla, Firmicutes, Bacteroidetes, Proteobacteria, Actinobacteria, Spirochaetes, and Fusobacteriacontained 99% of the taxa in all the samples analysed. Conclusion: Diversity of the microbiome in patients with CAD was similar to the normal human microbiome.

scholarly journals G2S: A New Deep Learning Tool for Predicting Stool Microbiome Structure From Oral Microbiome Data

2021 ◽  
Vol 12 ◽  
Author(s):  
Simone Rampelli ◽  
Marco Fabbrini ◽  
Marco Candela ◽  
Elena Biagi ◽  
Patrizia Brigidi ◽  
...  
Keyword(s):  
Deep Learning ◽  
Human Microbiome ◽  
Oral Microbiome ◽  
Fecal Microbiome ◽  
The Family ◽  
Bioinformatic Tool ◽  
Microbial Metagenomics ◽  
Community Theory ◽  
Microbiome Data ◽  
Fecal Sampling

Deep learning methodologies have revolutionized prediction in many fields and show the potential to do the same in microbial metagenomics. However, deep learning is still unexplored in the field of microbiology, with only a few software designed to work with microbiome data. Within the meta-community theory, we foresee new perspectives for the development and application of deep learning algorithms in the field of the human microbiome. In this context, we developed G2S, a bioinformatic tool for taxonomic prediction of the human fecal microbiome directly from the oral microbiome data of the same individual. The tool uses a deep convolutional neural network trained on paired oral and fecal samples from populations across the globe, which allows inferring the stool microbiome at the family level more accurately than other available approaches. The tool can be used in retrospective studies, where fecal sampling was not performed, and especially in the field of paleomicrobiology, as a unique opportunity to recover data related to ancient gut microbiome configurations. G2S was validated on already characterized oral and fecal sample pairs, and then applied to ancient microbiome data from dental calculi, to derive putative intestinal components in medieval subjects.

The Genetics and Genomics of Asthma

2018 ◽  
Vol 19 (1) ◽  
pp. 223-246 ◽  
Author(s):  
Saffron A.G. Willis-Owen ◽  
William O.C. Cookson ◽  
Miriam F. Moffatt
Keyword(s):  
Sequence Variation ◽  
Human Microbiome ◽  
Technological Advances ◽  
Genome Wide ◽  
A Genome ◽  
Wide Range ◽  
Health And Disease ◽  
Wide Scale ◽  
Genetics And Genomics ◽  
The Individual

Asthma is a common, clinically heterogeneous disease with strong evidence of heritability. Progress in defining the genetic underpinnings of asthma, however, has been slow and hampered by issues of inconsistency. Recent advances in the tools available for analysis—assaying transcription, sequence variation, and epigenetic marks on a genome-wide scale—have substantially altered this landscape. Applications of such approaches are consistent with heterogeneity at the level of causation and specify patterns of commonality with a wide range of alternative disease traits. Looking beyond the individual as the unit of study, advances in technology have also fostered comprehensive analysis of the human microbiome and its varied roles in health and disease. In this article, we consider the implications of these technological advances for our current understanding of the genetics and genomics of asthma.

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