Abundance and diversity of resistomes differ between healthy human oral cavities and gut

Carr, Victoria R.; Witherden, Elizabeth A.; Lee, Sunjae; Shoaie, Saeed; Mullany, Peter; Proctor, Gordon; Moyes, David L.

doi:10.1101/644922

Cited by 10 publications

(12 citation statements)

References 50 publications

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“…Antimicrobial resistance genes (ARGs) appear to be a natural feature of the oral microbiome, and is independent of antibiotic exposure to a large extent. 1 Consequently, the oral microbiome serves as a significant reservoir for these genes, which are transferred to pathogenic microbes by horizontal gene transfer (HGT). In the oral cavity, bacteria form biofilms, and this facilitates the acquisition of ARGs and their HGT.…”

Section: Introductionmentioning

confidence: 99%

Methicillin-Resistant Staphylococcus aureus in the Oral Cavity: Implications for Antibiotic Prophylaxis and Surveillance

Donkor

Kotey

2020

Infect Dis (Auckl)

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The oral cavity harbors a multitude of commensal flora, which may constitute a repository of antibiotic resistance determinants. In the oral cavity, bacteria form biofilms, and this facilitates the acquisition of antibiotic resistance genes through horizontal gene transfer. Recent reports indicate high methicillin-resistant Staphylococcus aureus (MRSA) carriage rates in the oral cavity. Establishment of MRSA in the mouth could be enhanced by the wide usage of antibiotic prophylaxis among at-risk dental procedure candidates. These changes in MRSA epidemiology have important implications for MRSA preventive strategies, clinical practice, as well as the methodological approaches to carriage studies of the organism.

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Section: Introductionmentioning

confidence: 99%

Methicillin-Resistant Staphylococcus aureus in the Oral Cavity: Implications for Antibiotic Prophylaxis and Surveillance

Donkor

Kotey

2020

Infect Dis (Auckl)

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“…Since the Spearman correlation analysis is most commonly used in resistome studies [65] and seems to perform overall better than other approaches in identifying pairwise associations between omics data, it has been present as a first choice in ResistoXplorer [66]. In particular, features (ARGs or taxa) that are not present in half of the samples across all the groups are removed to eliminate an artificial association bias before performing Spearman correlation analysis [65,67]. By default, these approaches (except CCLasso) use the microbiome and resistome relative abundances (proportions) for correlation inference.…”

Section: Integrative Analysismentioning

confidence: 99%

“…AMR++ Shiny [15] is a web-based R/shiny application dedicated for basic exploratory and statistical analysis of metagenomic resistome and microbiome data. More recently, resistomeAnalysis [67] R package also supports visualization, comparative and integrative analysis of resistome abundance profile.…”

Section: Comparison With Other Toolsmentioning

confidence: 99%

ResistoXplorer: a web-based tool for visual, statistical and exploratory data analysis of resistome data

Dhariwal

Junges

Chen

et al. 2020

Preprint

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Background The study of resistomes using whole metagenomic sequencing enables access to the large repertoire of resistance genes usually found in complex microbial communities, such as the human microbiome. Over recent years, sophisticated and diverse pipelines have been established to facilitate raw data processing and annotation. Despite the progress, there are no easy-to-use tools for comprehensive visual, statistical, and functional analysis of resistome data. Thus, exploration of the resulting large complex datasets remains a key bottleneck requiring robust computational resources and technical expertise, which creates a significant hurdle for advancements in the field. Results Here, we introduce ResistoXplorer, a user-friendly tool that integrates recent advancements in statistics and visualization, coupled with extensive functional annotations and phenotype collection, to enable high-throughput analysis of common outputs generated from resistome studies. ResistoXplorer contains three modules- the Antimicrobial Resistance Gene Table module offers various options for composition profiling, functional profiling and comparative analysis of resistome data; the Integration module supports integrative exploratory analysis of resistome and microbiome abundance profiles in metagenomic samples; finally, the Antimicrobial Resistance Gene List module enables users to explore antimicrobial resistance genes according to function and potential microbial hosts using visual analytics to gain biological insights. Within these three modules, ResistoXplorer offers comprehensive assistance for ARG functional annotations along with their microbe and phenotype associations based on data collected from >10 reference databases. In addition, it provides support for a variety of methods for composition profiling, visualization and exploratory data analysis, as well as extensive support for various data normalization methods and machine learning algorithms for identification of resistome signatures.Finally, ResistoXplorer offers also network visualization for intuitive exploration of associations between antimicrobial resistance genes and the microbial hosts, incorporated with functional enrichment analysis support. Conclusions ResistoXplorer is a web-based tool with a user-friendly interface that enables comprehensive and real-time downstream analysis of resistome data. As such, it allows for in-depth exploration of metagenomic datasets focusing on the intrinsic networks and correlations of antimicrobial resistance genes and their underlying microbial determinants. ResistoXplorer will assist researchers and clinicians in the field of AMR to facilitate discovery in large-scale and multi-dimensional metagenomic datasets. ResistoXplorer is publicly available at http://resistoxplorer.no/ResistoXplorer/.

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“…There has been increased interest in the role of the microbiome in human disease with the completion of the Human Microbiome Project (Human Microbiome Project Consortium 2012). While the majority of microbiome research has initially focused on the gut microbiome, there has been increasing research into other regions, including the skin, vaginal, and oral microbiomes, as well as recent recognition of oral-systemic axes of crosstalk, including the oral-gut axis (Schmidt et al 2019; Carr et al 2020). Within the oral microbiome, there has been significant interest in the role of oral dysbiosis in causing disease.…”

Section: Introductionmentioning

confidence: 99%

Inflammatory Networks Linking Oral Microbiome with Systemic Health and Disease

2020

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The dance between microbes and the immune system takes place in all biological systems, including the human body, but this interaction is especially complex in the primary gateway to the body: the oral cavity. Recent advances in technology have enabled deep sequencing and analysis of members and signals of these communities. In a healthy state, the oral microbiome is composed of commensals, and their genes and phenotypes may be selected by the immune system to survive in symbiosis. These highly regulated signals are modulated by a network of microbial and host metabolites. However, in a diseased state, host-microbial networks lead to dysbiosis and considerable burden to the host prior to systemic impact that extends beyond the oral compartment. Interestingly, we presented data demonstrating similarities between human and mice immune dysbiosis and discussed how this affects the host response to similar pathobionts. The host and microbial signatures of a number of disease states are currently being examined to identify potential correlations. How the oral microbiome interacts with inflammation and the immune system to cause disease remains an area of active research. In this review, we summarize recent advancements in understanding the role of oral microbiota in mediating inflammation and altering systemic health and disease. In line with these findings, it is possible that existing conditions may be resolved by targeting specific immune-microbial markers in a positive way.

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Abundance and diversity of resistomes differ between healthy human oral cavities and gut

Cited by 10 publications

References 50 publications

Methicillin-Resistant Staphylococcus aureus in the Oral Cavity: Implications for Antibiotic Prophylaxis and Surveillance

Methicillin-Resistant Staphylococcus aureus in the Oral Cavity: Implications for Antibiotic Prophylaxis and Surveillance

ResistoXplorer: a web-based tool for visual, statistical and exploratory data analysis of resistome data

Inflammatory Networks Linking Oral Microbiome with Systemic Health and Disease

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