Identification Of Microbiome Research Articles

Microbial Diversity in the Early In Vivo-Formed Dental Biofilm.

Although the mature dental biofilm composition is well studied, there is very little information on the earliest phase of in vivo tooth colonization. Progress in dental biofilm collection methodologies and techniques of large-scale microbial identification have made new studies in this field of oral biology feasible. The aim of this study was to characterize the temporal changes and diversity of the cultivable and noncultivable microbes in the early dental biofilm. Samples of early dental biofilm were collected from 11 healthy subjects at 0, 2, 4, and 6 h after removal of plaque and pellicle from tooth surfaces. With the semiquantitative Human Oral Microbiome Identification Microarray (HOMIM) technique, which is based on 16S rRNA sequence hybridizations, plaque samples were analyzed with the currently available 407 HOMIM microbial probes. This led to the identification of at least 92 species, with streptococci being the most abundant bacteria across all time points in all subjects. High-frequency detection was also made with Haemophilus parainfluenzae, Gemella haemolysans, Slackia exigua, and Rothia species. Abundance changes over time were noted for Streptococcus anginosus and Streptococcus intermedius (P = 0.02), Streptococcus mitis bv. 2 (P = 0.0002), Streptococcus oralis (P = 0.0002), Streptococcus cluster I (P = 0.003), G. haemolysans (P = 0.0005), and Stenotrophomonas maltophilia (P = 0.02). Among the currently uncultivable microbiota, eight phylotypes were detected in the early stages of biofilm formation, one belonging to the candidate bacterial division TM7, which has attracted attention due to its potential association with periodontal disease.

Association of Synergistetes and Cyclodipeptides with Periodontitis

The purpose of this study was to evaluate the microbial community (MC) composition as it relates to salivary metabolites and periodontal clinical parameters in a 21-d biofilm-overgrowth model. Subjects (N = 168) were enrolled equally into 5 categories of periodontal status per the biofilm-gingival interface classification. Microbial species within subgingival plaque samples were identified by human microbiome identification microarray. Whole saliva was analyzed by liquid chromatography–mass spectrometry and gas chromatography–mass spectrometry for metabolite identification. Phylum was grouped into MCs according to principal component analysis. Generalized linear and regression models were used to examine the association among MC, species, periodontal clinical parameters, and salivary metabolome. Multiple comparisons were adjusted with the false discovery rate. The study population was distributed into 8 distinct MC profiles, designated MC-1 to MC-8. MC-2 explained 14% of the variance and was dominated by Synergistetes and Spirochaetes. It was the only community structure significantly associated with high probing depth (P = 0.02) and high bleeding on probing (P = 0.008). MC-2 was correlated with traditional periodontal pathogens and several newly identified putative periodontal pathogens: Fretibacterium fastidiosum, Fretibacterium sp. OT360/OT362, Filifactor alocis, Treponema lecithinolyticum, Eubacterium saphenum, Desulfobulbus sp./OT041, and Mogibacterium timidum. Synergistetes phylum was strongly associated with 2 novel metabolites—cyclo (-leu-pro) and cyclo (-phe-pro)—at 21 d of biofilm overgrowth (P = 0.02). In subjects with severe periodontitis (P2 and P3), cyclo (-leu-pro) and cyclo (-phe-pro) were significantly associated with increased changes in probing depth at 21 d of biofilm overgrowth (P ≤ 0.05). The analysis identified a MC dominated by Synergistetes, with classic and putative newly identified pathogens/pathobionts associated with clinical disease. The metabolomic discovery of 2 novel cyclodipeptides that have been reported to serve as quorum-sensing and/or bacteriocidal/bacteriostatic molecules, in association with Synergistetes, suggests a potential role in periodontal biofilm dysbiosis and periodontal disease that warrants further investigation.

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Introduction: Current culture-based techniques may be inadequate for identifying causative agents in patients with ventilator-associated pneumonia (VAP). We used a culture-independent molecular approach to assess the bacterial species colonizing the aerodigestive tract of mechanically ventilated children. Hypothesis: We hypothesized that culture-independent methods would identify phylotypes and difficult-to-grow species that are not detected by routine culture. These data may shed new light on the differences in the oral microbiome between age groups and might uncover novel VAP-associated pathogens. Methods: Oral swabs as well as tracheal and gastric aspirates were obtained sequentially from mechanically ventilated children (<18 years) in the ICU following elective surgery. Samples were sent for routine bacterial culture and DNA isolation for PCR amplification of 16S rRNA genes followed by analysis using a previously validated microarray (HOMIM). Results: We analyzed 97 clinical samples from 14 subjects (50% female, mean 5.6 years) following cardiac (n=10) and spinal fusion surgery (n=4). Routine cultures revealed 4 potential bacterial pathogens in 6 samples from 2 subjects. PCR amplification of 16S rRNA genes was successful in 28 samples (29%). Over 100 distinct taxa were detected on microarray analysis. The oral microbiome burden was significantly higher in older children compared to infants <12 months (p<0.05 by Wilcoxon rank sum test). Microbial profiles were also distinct between the 2 groups. One subject had VAP, and growth of Pseudomonas aeruginosa from tracheal aspirate was mirrored by molecular detection of the organism first in oral and then tracheal samples during the study. Conclusions: Culture-independent molecular methods using 16S rRNA gene sequences allowed identification of known VAP-associated pathogens and a variety of unculturable microbes in oral, tracheal and gastric samples. The clinical significance of these taxa warrants further investigation. Edentulate infants have a lower microbiome burden and distinct profile compared to older children. Microbiome identification may guide bedside practices in the ICU, such as oral hygiene, and enhance our understanding of VAP pathogenesis.

Oral microbiome profiles: 16S rRNA pyrosequencing and microarray assay comparison.

ObjectivesThe human oral microbiome is potentially related to diverse health conditions and high-throughput technology provides the possibility of surveying microbial community structure at high resolution. We compared two oral microbiome survey methods: broad-based microbiome identification by 16S rRNA gene sequencing and targeted characterization of microbes by custom DNA microarray.MethodsOral wash samples were collected from 20 individuals at Memorial Sloan-Kettering Cancer Center. 16S rRNA gene survey was performed by 454 pyrosequencing of the V3–V5 region (450 bp). Targeted identification by DNA microarray was carried out with the Human Oral Microbe Identification Microarray (HOMIM). Correlations and relative abundance were compared at phylum and genus level, between 16S rRNA sequence read ratio and HOMIM hybridization intensity.ResultsThe major phyla, Firmicutes, Proteobacteria, Bacteroidetes, Actinobacteria, and Fusobacteria were identified with high correlation by the two methods (r = 0.70∼0.86). 16S rRNA gene pyrosequencing identified 77 genera and HOMIM identified 49, with 37 genera detected by both methods; more than 98% of classified bacteria were assigned in these 37 genera. Concordance by the two assays (presence/absence) and correlations were high for common genera (Streptococcus, Veillonella, Leptotrichia, Prevotella, and Haemophilus; Correlation = 0.70–0.84).ConclusionMicrobiome community profiles assessed by 16S rRNA pyrosequencing and HOMIM were highly correlated at the phylum level and, when comparing the more commonly detected taxa, also at the genus level. Both methods are currently suitable for high-throughput epidemiologic investigations relating identified and more common oral microbial taxa to disease risk; yet, pyrosequencing may provide a broader spectrum of taxa identification, a distinct sequence-read record, and greater detection sensitivity.