scholarly journals Assessing the impact of dental and periodontal statuses on the salivary microbiome: a global oral health scale

2020 ◽  
Author(s):  
Marta Relvas ◽  
Alba Regueira-Iglesias ◽  
Carlos Balsa-Castro ◽  
Filomena Salazar ◽  
Jose Julio Pacheco ◽  
...  
Keyword(s):  
Oral Health ◽  
Bacterial Community ◽  
16S Rrna ◽  
Oral Disease ◽  
Rrna Gene ◽  
Convenience Sample ◽  
Core Microbiome ◽  
Rdna Sequencing ◽  
Salivary Microbiota ◽  
The Impact

Very few 16S rRNA-based studies have conducted a simultaneous analysis to identify the impact of various dental and periodontal parameters and determine which of them have the greatest repercussion for the salivary microbiota. Consequently, this study used 16S rRNA gene amplicon sequencing to assess the impact on salivary microbiome of different grades of dental, periodontal and global oral disease. Our global oral health scale was used to produce a convenience sample of 81 patients from 270 who were initially recruited. These subjects were assigned the following grades: 47 had a periodontal grade (PG) of 0 and dental grades (DGs) between 0-3, and 46 had a DG of 0 and PGs between 0-3. Saliva samples were collected from each participant. Sequencing was performed in Illumina MiSeq with 2 x 300 bp reads, while the raw reads were processed according to the Mothur pipeline. The statistical analysis of the 16S rDNA sequencing data at the species level was conducted using the Phyloseq, DESeq2 and Microbiome packages. The impact on the salivary microbiota of the different DGs, PGs and global oral grades (GGs) was investigated in relation to: 1) indicators of alpha diversity and the structure of the bacterial community; and 2) the composition of the core microbiome and the results of differential abundance tests. The simultaneous presence of dental and periodontal pathology has a potentiating effect on the richness and diversity of the salivary microbiota. The structure of the bacterial community in oral health differs from that present in dental, periodontal or global oral disease, especially in high grades. The non-specific microbiome core contains a greater number of more abundant species than the specific core of a particular dental or periodontal condition (health or pathology). The number of taxa in the salivary microbiota with differential abundances between the DGs, PGs or GGs represents, at most, a quarter of the bacterial community and are mainly non-core species. Supragingival dental parameters influence the microbiota`s abundance more than subgingival periodontal parameters, with the former making a greater contribution to the impact that global oral health has on salivary microbiome.

scholarly journals Relationship between dental and periodontal health status and the salivary microbiome: bacterial diversity, co-occurrence networks and predictive models

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
M. Relvas ◽  
A. Regueira-Iglesias ◽  
C. Balsa-Castro ◽  
F. Salazar ◽  
J. J. Pacheco ◽  
...  
Keyword(s):  
Oral Health ◽  
Periodontal Disease ◽  
Bacterial Diversity ◽  
Predictive Models ◽  
Oral Disease ◽  
Rrna Gene ◽  
Convenience Sample ◽  
Core Microbiome ◽  
Rdna Sequencing ◽  
The Impact

AbstractThe present study used 16S rRNA gene amplicon sequencing to assess the impact on salivary microbiome of different grades of dental and periodontal disease and the combination of both (hereinafter referred to as oral disease), in terms of bacterial diversity, co-occurrence network patterns and predictive models. Our scale of overall oral health was used to produce a convenience sample of 81 patients from 270 who were initially recruited. Saliva samples were collected from each participant. Sequencing was performed in Illumina MiSeq with 2 × 300 bp reads, while the raw reads were processed according to the Mothur pipeline. The statistical analysis of the 16S rDNA sequencing data at the species level was conducted using the phyloseq, DESeq2, Microbiome, SpiecEasi, igraph, MixOmics packages. The simultaneous presence of dental and periodontal pathology has a potentiating effect on the richness and diversity of the salivary microbiota. The structure of the bacterial community in oral health differs from that present in dental, periodontal or oral disease, especially in high grades. Supragingival dental parameters influence the microbiota’s abundance more than subgingival periodontal parameters, with the former making a greater contribution to the impact that oral health has on the salivary microbiome. The possible keystone OTUs are different in the oral health and disease, and even these vary between dental and periodontal disease: half of them belongs to the core microbiome and are independent of the abundance parameters. The salivary microbiome, involving a considerable number of OTUs, shows an excellent discriminatory potential for distinguishing different grades of dental, periodontal or oral disease; considering the number of predictive OTUs, the best model is that which predicts the combined dental and periodontal status.

scholarly journals Impact of Diagnosed and Undiagnosed Respiratory Pseudomonas on VAP and VAE During Long-Term Acute Care

2020 ◽  
Vol 41 (S1) ◽  
pp. s258-s259
Author(s):  
James Harrigan ◽  
Ebbing Lautenbach ◽  
Emily Reesey ◽  
Magda Wernovsky ◽  
Pam Tolomeo ◽  
...  
Keyword(s):  
Bacterial Community ◽  
Acute Care ◽  
Statistical Significance ◽  
Rrna Gene ◽  
Care Hospital ◽  
16S Sequencing ◽  
Increased Risk ◽  
Wide Range ◽  
The Impact

Background: Clinically diagnosed ventilator-associated pneumonia (VAP) is common in the long-term acute-care hospital (LTACH) setting and may contribute to adverse ventilator-associated events (VAEs). Pseudomonas aeruginosa is a common causative organism of VAP. We evaluated the impact of respiratory P. aeruginosa colonization and bacterial community dominance, both diagnosed and undiagnosed, on subsequent P. aeruginosa VAP and VAE events during long-term acute care. Methods: We enrolled 83 patients on LTACH admission for ventilator weaning, performed longitudinal sampling of endotracheal aspirates followed by 16S rRNA gene sequencing (Illumina HiSeq), and bacterial community profiling (QIIME2). Statistical analysis was performed with R and Stan; mixed-effects models were fit to relate the abundance of respiratory Psa on admission to clinically diagnosed VAP and VAE events. Results: Of the 83 patients included, 12 were diagnosed with P. aeruginosa pneumonia during the 14 days prior to LTACH admission (known P. aeruginosa), and 22 additional patients received anti–P. aeruginosa antibiotics within 48 hours of admission (suspected P. aeruginosa); 49 patients had no known or suspected P. aeruginosa (unknown P. aeruginosa). Among the known P. aeruginosa group, all 12 patients had P. aeruginosa detectable by 16S sequencing, with elevated admission P. aeruginosa proportional abundance (median, 0.97; IQR, 0.33–1). Among the suspected P. aeruginosa group, all 22 patients had P. aeruginosa detectable by 16S sequencing, with a wide range of admission P. aeruginosa proportional abundance (median, 0.0088; IQR, 0.00012–0.31). Of the 49 patients in the unknown group, 47 also had detectable respiratory Psa, and many had high P. aeruginosa proportional abundance at admission (median, 0.014; IQR, 0.00025–0.52). Incident P. aeruginosa VAP was observed within 30 days in 4 of the known P. aeruginosa patients (33.3%), 5 of the suspected P. aeruginosa patients (22.7%), and 8 of the unknown P. aeruginosa patients (16.3%). VAE was observed within 30 days in 1 of the known P. aeruginosa patients (8.3%), 2 of the suspected P. aeruginosa patients (9.1%), and 1 of the unknown P. aeruginosa patients (2%). Admission P. aeruginosa abundance was positively associated with VAP and VAE risk in all groups, but the association only achieved statistical significance in the unknown group (type S error <0.002 for 30-day VAP and <0.011 for 30-day VAE). Conclusions: We identified a high prevalence of unrecognized respiratory P. aeruginosa colonization among patients admitted to LTACH for weaning from mechanical ventilation. The admission P. aeruginosa proportional abundance was strongly associated with increased risk of incident P. aeruginosa VAP among these patients.Funding: NoneDisclosures: None

scholarly journals 16S rRNA gene and 18S rRNA gene diversity in microbial mat communities in meltwater ponds on the McMurdo Ice Shelf, Antarctica

Polar Biology ◽  
2021 ◽  
Author(s):  
Eleanor E. Jackson ◽  
Ian Hawes ◽  
Anne D. Jungblut
Keyword(s):  
16S Rrna ◽  
18S Rrna ◽  
High Throughput Sequencing ◽  
Microbial Mats ◽  
Gene Diversity ◽  
Salinity Gradient ◽  
18S Rrna Gene ◽  
Rrna Gene ◽  
Ice Shelf ◽  
The Impact

AbstractThe undulating ice of the McMurdo Ice Shelf, Southern Victoria Land, supports one of the largest networks of ice-based, multiyear meltwater pond habitats in Antarctica, where microbial mats are abundant and contribute most of the biomass and biodiversity. We used 16S rRNA and 18S rRNA gene high-throughput sequencing to compare variance of the community structure in microbial mats within and between ponds with different salinities and pH. Proteobacteria and Cyanobacteria were the most abundant phyla, and composition at OTU level was highly specific for the meltwater ponds with strong community sorting along the salinity gradient. Our study provides the first detailed evaluation of eukaryote communities for the McMurdo Ice Shelf using the 18S rRNA gene. They were dominated by Ochrophyta, Chlorophyta and Ciliophora, consistent with previous microscopic analyses, but many OTUs belonging to less well-described heterotrophic protists from Antarctic ice shelves were also identified including Amoebozoa, Rhizaria and Labyrinthulea. Comparison of 16S and 18S rRNA gene communities showed that the Eukaryotes had lower richness and greater similarity between ponds in comparison with Bacteria and Archaea communities on the McMurdo Ice shelf. While there was a weak correlation between community dissimilarity and geographic distance, the congruity of microbial assemblages within ponds, especially for Bacteria and Archaea, implies strong habitat filtering in ice shelf meltwater pond ecosystems, especially due to salinity. These findings help to understand processes that are important in sustaining biodiversity and the impact of climate change on ice-based aquatic habitats in Antarctica.

scholarly journals Comparison of Respiratory Microbiome Disruption Indices to Predict VAP and VAE risk at LTACH Admission

2020 ◽  
Vol 41 (S1) ◽  
pp. s179-s180
Author(s):  
Erik Clarke ◽  
Kathleen None Chiotos ◽  
James Harrigan ◽  
Ebbing Lautenbach ◽  
Emily Reesey ◽  
...  
Keyword(s):  
Critical Illness ◽  
Bacterial Community ◽  
16S Rrna ◽  
Respiratory Tract ◽  
Predictive Performance ◽  
Community Diversity ◽  
Rrna Gene ◽  
Sequence Variant ◽  
Antibiotic Exposure ◽  
Shannon Diversity

Background: Healthcare exposure results in significant microbiome disruption, particularly in the setting of critical illness, which may contribute to risk for healthcare-associated infections (HAIs). Patients admitted to long-term acute-care hospitals (LTACHs) have extensive prior healthcare exposure and critical illness; significant microbiome disruption has been previously documented among LTACH patients. We compared the predictive value of 3 respiratory tract microbiome disruption indices—bacterial community diversity, dominance, and absolute abundance—as they relate to risk for ventilator-associated pneumonia (VAP) and adverse ventilator-associated events (VAE), which commonly complicate LTACH care. Methods: We enrolled 83 subjects on admission to an academic LTACH for ventilator weaning and performed longitudinal sampling of endotracheal aspirates, followed by 16S rRNA gene sequencing (Illumina HiSeq), bacterial community profiling (QIIME2) for diversity, and 16S rRNA quantitative PCR (qPCR) for total bacterial abundance. Statistical analyses were performed with R and Stan software. Mixed-effects models were fit to relate the admission MDIs to subsequent clinically diagnosed VAP and VAE. Results: Of the 83 patients, 19 had been diagnosed with pneumonia during the 14 days prior to LTACH admission (ie, “recent past VAP”); 23 additional patients were receiving antibiotics consistent with empiric VAP therapy within 48 hours of admission (ie, “empiric VAP therapy”); and 41 patients had no evidence of VAP at admission (ie, “no suspected VAP”). We detected no statistically significant differences in admission Shannon diversity, maximum amplicon sequence variant (ASV)–level proportional abundance, or 16S qPCR across the variables of interest. In isolation, all 3 admission microbiome disruption indices showed poor predictive performance, though Shannon diversity performed better than maximum ASV abundance. Predictive models that combined (1) bacterial diversity or abundance with (2) recent prior VAP diagnosis and (3) concurrent antibiotic exposure best predicted 14-day VAP (type S error < 0.05) and 30-day VAP (type S error < 0.003). In this cohort, VAE risk was paradoxically associated with higher admission Shannon diversity and lower admission maximum ASV abundance. Conclusions: In isolation, respiratory tract microbiome disruption indices obtained at LTACH admission showed poor predictive performance for subsequent VAP and VAE. But diversity and abundance models incorporating recent VAP history and admission antibiotic exposure performed well predicting 14-day and 30-day VAP.Disclosures: NoneFunding: None

scholarly journals Exploring protocol bias in airway microbiome studies: one versus two PCR steps and 16S rRNA gene region V3 V4 versus V4

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Christine Drengenes ◽  
Tomas M. L. Eagan ◽  
Ingvild Haaland ◽  
Harald G. Wiker ◽  
Rune Nielsen
Keyword(s):  
16S Rrna ◽  
16S Rrna Gene ◽  
Bacterial Load ◽  
Marker Gene ◽  
Gene Region ◽  
Lower Airway ◽  
Rrna Gene ◽  
Wide Range ◽  
Airway Microbiome ◽  
The Impact

Abstract Background Studies on the airway microbiome have been performed using a wide range of laboratory protocols for high-throughput sequencing of the bacterial 16S ribosomal RNA (16S rRNA) gene. We sought to determine the impact of number of polymerase chain reaction (PCR) steps (1- or 2- steps) and choice of target marker gene region (V3 V4 and V4) on the presentation of the upper and lower airway microbiome. Our analyses included lllumina MiSeq sequencing following three setups: Setup 1 (2-step PCR; V3 V4 region), Setup 2 (2-step PCR; V4 region), Setup 3 (1-step PCR; V4 region). Samples included oral wash, protected specimen brushes and protected bronchoalveolar lavage (healthy and obstructive lung disease), and negative controls. Results The number of sequences and amplicon sequence variants (ASV) decreased in order setup1 > setup2 > setup3. This trend appeared to be associated with an increased taxonomic resolution when sequencing the V3 V4 region (setup 1) and an increased number of small ASVs in setups 1 and 2. The latter was considered a result of contamination in the two-step PCR protocols as well as sequencing across multiple runs (setup 1). Although genera Streptococcus, Prevotella, Veillonella and Rothia dominated, differences in relative abundance were observed across all setups. Analyses of beta-diversity revealed that while oral wash samples (high biomass) clustered together regardless of number of PCR steps, samples from the lungs (low biomass) separated. The removal of contaminants identified using the Decontam package in R, did not resolve differences in results between sequencing setups. Conclusions Differences in number of PCR steps will have an impact of final bacterial community descriptions, and more so for samples of low bacterial load. Our findings could not be explained by differences in contamination levels alone, and more research is needed to understand how variations in PCR-setups and reagents may be contributing to the observed protocol bias.

scholarly journals The bacterial community of the lone star tick (Amblyomma americanum)

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
L. Paulina Maldonado-Ruiz ◽  
Saraswoti Neupane ◽  
Yoonseong Park ◽  
Ludek Zurek
Keyword(s):  
Bacterial Community ◽  
Amblyomma Americanum ◽  
Rrna Gene ◽  
Culturable Bacteria ◽  
Core Microbiome ◽  
Lone Star Tick ◽  
Animal Pathogens ◽  
Wide Range ◽  
Culture Independent ◽  
Culture Dependent

Abstract Background The lone star tick (Amblyomma americanum), an important vector of a wide range of human and animal pathogens, is very common throughout the East and Midwest of the USA. Ticks are known to carry non-pathogenic bacteria that may play a role in their vector competence for pathogens. Several previous studies using the high throughput sequencing (HTS) technologies reported the commensal bacteria in a tick midgut as abundant and diverse. In contrast, in our preliminary survey of the field collected adult lone star ticks, we found the number of culturable/viable bacteria very low. Methods We aimed to analyze the bacterial community of A. americanum by a parallel culture-dependent and a culture-independent approach applied to individual ticks. Results We analyzed 94 adult females collected in eastern Kansas and found that 60.8% of ticks had no culturable bacteria and the remaining ticks carried only 67.7 ± 42.8 colony-forming units (CFUs)/tick representing 26 genera. HTS of the 16S rRNA gene resulted in a total of 32 operational taxonomic units (OTUs) with the dominant endosymbiotic genera Coxiella and Rickettsia (> 95%). Remaining OTUs with very low abundance were typical soil bacterial taxa indicating their environmental origin. Conclusions No correlation was found between the CFU abundance and the relative abundance from the culture-independent approach. This suggests that many culturable taxa detected by HTS but not by culture-dependent method were not viable or were not in their culturable state. Overall, our HTS results show that the midgut bacterial community of A. americanum is very poor without a core microbiome and the majority of bacteria are endosymbiotic.

scholarly journals Diversity and Structure of the Endophytic Bacterial Communities Associated With Three Terrestrial Orchid Species as Revealed by 16S rRNA Gene Metabarcoding

2020 ◽  
Vol 11 ◽  
Author(s):  
Pasquale Alibrandi ◽  
Sylvia Schnell ◽  
Silvia Perotto ◽  
Massimiliano Cardinale
Keyword(s):  
Bacterial Community ◽  
16S Rrna ◽  
16S Rrna Gene ◽  
Host Plant ◽  
Bacterial Communities ◽  
Reproductive Organs ◽  
Distribution Model ◽  
Rrna Gene ◽  
Orchid Species ◽  
Core Microbiota

The endophytic microbiota can establish mutualistic or commensalistic interactions within the host plant tissues. We investigated the bacterial endophytic microbiota in three species of Mediterranean orchids (Neottia ovata, Serapias vomeracea, and Spiranthes spiralis) by metabarcoding of the 16S rRNA gene. We examined whether the different orchid species and organs, both underground and aboveground, influenced the endophytic bacterial communities. A total of 1,930 operational taxonomic units (OTUs) were obtained, mainly Proteobacteria and Actinobacteria, whose distribution model indicated that the plant organ was the main determinant of the bacterial community structure. The co-occurrence network was not modular, suggesting a relative homogeneity of the microbiota between both plant species and organs. Moreover, the decrease in species richness and diversity in the aerial vegetative organs may indicate a filtering effect by the host plant. We identified four hub OTUs, three of them already reported as plant-associated taxa (Pseudoxanthomonas, Rhizobium, and Mitsuaria), whereas Thermus was an unusual member of the plant microbiota. Core microbiota analysis revealed a selective and systemic ascent of bacterial communities from the vegetative to the reproductive organs. The core microbiota was also maintained in the S. spiralis seeds, suggesting a potential vertical transfer of the microbiota. Surprisingly, some S. spiralis seed samples displayed a very rich endophytic microbiota, with a large number of OTUs shared with the roots, a situation that may lead to a putative restoring process of the root-associated microbiota in the progeny. Our results indicate that the bacterial community has adapted to colonize the orchid organs selectively and systemically, suggesting an active involvement in the orchid holobiont.

Characterization of bacterial community structure dynamics in a rat burn wound model using 16S rRNA gene sequencing

2022 ◽  
Author(s):  
Chen Zheng-li ◽  
Peng Yu ◽  
Wu Guo-sheng ◽  
Hong Xu-Dong ◽  
Fan Hao ◽  
...  
Keyword(s):  
Community Structure ◽  
Bacterial Community ◽  
16S Rrna ◽  
16S Rrna Gene ◽  
Bacterial Community Structure ◽  
Bacterial Species ◽  
16S Rrna Gene Sequencing ◽  
Rrna Gene ◽  
Sprague Dawley ◽  
Rrna Gene Sequencing

Abstract Burns destroy the skin barrier and alter the resident bacterial community, thereby facilitating bacterial infection. To treat a wound infection, it is necessary to understand the changes in the wound bacterial community structure. However, traditional bacterial cultures allow the identification of only readily growing or purposely cultured bacterial species and lack the capacity to detect changes in the bacterial community. In this study, 16S rRNA gene sequencing was used to detect alterations in the bacterial community structure in deep partial-thickness burn wounds on the back of Sprague-Dawley rats. These results were then compared with those obtained from the bacterial culture. Bacterial samples were collected prior to wounding and 1, 7, 14, and 21 days after wounding. The 16S rRNA gene sequence analysis showed that the number of resident bacterial species decreased after the burn. Both resident bacterial richness and diversity, which were significantly reduced after the burn, recovered following wound healing. The dominant resident strains also changed, but the inhibition of bacterial community structure was in a non-volatile equilibrium state, even in the early stage after healing. Furthermore, the correlation between wound and environmental bacteria increased with the occurrence of burns. Hence, the 16S rRNA gene sequence analysis reflected the bacterial condition of the wounds better than the bacterial culture. 16S rRNA sequencing in the Sprague-Dawley rat burn model can provide more information for the prevention and treatment of burn infections in clinical settings and promote further development in this field.

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