Oral-gut 16S rRNA rat samples
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA680607 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR13162000.fastq.gz | Fastqsanger.gz | |||
| SRR13162001.fastq.gz | Fastqsanger.gz | |||
| SRR13162002.fastq.gz | Fastqsanger.gz | |||
| SRR13162003.fastq.gz | Fastqsanger.gz | |||
| SRR13162004.fastq.gz | Fastqsanger.gz |
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Project description: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.
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Project description:Microbiome of supragingival plaque from healthy volunteers
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Project description:A curated murine oral microbiome database to be used as a reference for mouse-based studies has been constructed using a combination of bacterial culture, 16S rRNA gene amplicon, and whole-genome sequencing. The database comprises a collection of nearly full-length 16S rRNA gene sequences from cultured isolates and draft genomes from representative taxa collected from a range of sources, including specific-pathogen-free laboratory mice, wild Mus musculus domesticus mice, and formerly wild wood mouse Apodemus sylvaticus At present, it comprises 103 mouse oral taxa (MOT) spanning four phyla-Firmicutes, Proteobacteria, Actinobacteria, and Bacteroidetes-including 12 novel undescribed species-level taxa. The key observations from this study are (i) the low diversity and predominantly culturable nature of the laboratory mouse oral microbiome and (ii) the identification of three major murine-specific oral bacterial lineages, namely, Streptococcus danieliae (MOT10), Lactobacillus murinus (MOT93), and Gemella species 2 (MOT43), which is one of the novel, still-unnamed taxa. Of these, S. danieliae is of particular interest, since it is a major component of the oral microbiome from all strains of healthy and periodontally diseased laboratory mice, as well as being present in wild mice. It is expected that this well-characterized database should be a useful resource for in vitro experimentation and mouse model studies in the field of oral microbiology.IMPORTANCE Mouse model studies are frequently used in oral microbiome research, particularly to investigate diseases such as periodontitis and caries, as well as other related systemic diseases. We have reported here the details of the development of a curated reference database to characterize the oral microbial community in laboratory and some wild mice. The genomic information and findings reported here can help improve the outcomes and accuracy of host-microbe experimental studies that use murine models to understand health and disease. Work is also under way to make the reference data sets publicly available on a web server to enable easy access and downloading for researchers across the world.
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Project description:The advent of next-generation sequencing has significantly facilitated characterization of the oral microbiome. Despite great efforts in streamlining the processes of sequencing and data curation, upstream steps required for amplicon library generation could still influence 16S rRNA gene-based microbial profiles. Among upstream processes, DNA extraction is a critical step that could represent a great source of bias. Accounting for bias introduced by extraction procedures is important when comparing studies that use different methods. Identifying the method that best portrays communities is also desirable. Accordingly, the aim of this study was to evaluate bias introduced by different DNA extraction procedures on oral microbiome profiles. Four DNA extraction methods were tested on mock communities consisting of seven representative oral bacteria. Additionally, supragingival plaque samples were collected from seven individuals and divided equally to test two commonly used DNA extraction procedures. Amplicon libraries of the 16S rRNA gene were generated and sequenced via 454-pyrosequencing. Evaluation of mock communities revealed that DNA yield and bacterial species representation varied with DNA extraction methods. Despite producing the lowest yield of DNA, a method that included bead beating was the only protocol capable of detecting all seven species in the mock community. Comparison of the performance of two commonly used methods (crude lysis and a chemical/enzymatic lysis+column-based DNA isolation) on plaque samples showed no effect of extraction protocols on taxa prevalence but global community structure and relative abundance of individual taxa were affected. At the phylum level, the latter method improved the recovery of Actinobacteria, Bacteroidetes, and Spirochaetes over crude lysis. DNA extraction distorts microbial profiles in simulated and clinical oral samples, reinforcing the importance of careful selection of a DNA extraction protocol to improve species recovery and facilitate data comparison across oral microbiology studies.
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Project description:Recent advances in genomic technologies have enabled more in-depth study of the oral microbiome. In this study, we compared the amplicons generated by primers targeting different sites of the 16S rRNA gene found in the Human Oral Microbiome Database (HOMD). Six sets of primer targeting V1-V2, V1-V3, V3-V4, V4-V5, V5-V7 and V6-V8 regions of 16S rRNA were tested via in silico simulation. Primers targeting the V1-V2, V3-V4, and V4-V5 regions generated more than 90% of the original input sequences. Primers targeting the V1-V2 and V1-V3 regions exhibited a low number of mismatches and unclassified sequences at the taxonomic level, but there were notable discrepancies at the species level. Phylogenetic tree comparisons showed primers targeting the V1-V2 and V3-V4 regions showed performances similar to primers targeting the whole 16s RNA region in terms of separating total oral microbiomes and periodontopathogens. In an analysis of clinical oral samples, V1-V2 primers showed superior performance for identifying more taxa and had better resolution sensitivity for Streptococcus than V3-V4 primers. In conclusion, primers targeting the V1-V2 region of 16S rRNA showed the best performance for oral microbiome studies. In addition, the study demonstrates the need for careful PCR primer selections.
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Project description:Tumor microenvironment (TME)-induced nanocatalytic therapy is a promising strategy for cancer treatment, but the low catalytic efficiency limits its therapeutic efficacy. Single-atom catalysts (SACs) are a new type of nanozyme with incredible catalytic efficiency. Here we construct a single-atom manganese (Mn)-N/C nanozyme. Mn-N/C catalyzes the conversion of cellular H2O2 to ∙OH through a Fenton-like reaction and enables the sufficient generation of reactive oxygen species (ROS), which induces immunogenic cell death (ICD) of tumor cells and significantly promotes CD8+T anti-tumor immunity. Moreover, RNA sequencing reveals that Mn-N/C treatment activates type I interferon (IFN) signaling which is critical for Mn-N/C-mediated anti-tumor immune response. Mechanistically, Mn-N/C-triggered releasing of cytosolic DNA from ICD tumor cells activates cGAS-STING pathway, consequently stimulating type I IFN induction. We propose a new promising single-atom nanozyme with extraordinary catalytic activity, which enhances anti-tumor immune response and exhibits synergistic therapeutic effects when combined with anti-PD-L1 blockade.
2024-04-24 | GSE249852 | GEO
Project description: Not available
| S-EPMC1393246 | biostudies-literature
Project description:Amplification and sequencing of 16S amplicons are widely used for profiling the structure of oral microbiota. However, it remains not clear whether and to what degree DNA extraction and targeted 16S rRNA hypervariable regions influence the analysis. Based on a mock community consisting of five oral bacterial species in equal abundance, we compared the 16S amplicon sequencing results on the Illumina MiSeq platform from six frequently employed DNA extraction procedures and three pairs of widely used 16S rRNA hypervariable primers targeting different 16S rRNA regions. Technical reproducibility of selected 16S regions was also assessed. DNA extraction method exerted considerable influence on the observed bacterial diversity while hypervariable regions had a relatively minor effect. Protocols with beads added to the enzyme-mediated DNA extraction reaction produced more accurate bacterial community structure than those without either beads or enzymes. Hypervariable regions targeting V3-V4 and V4-V5 seemed to produce more reproducible results than V1-V3. Neither sequencing batch nor change of operator affected the reproducibility of bacterial diversity profiles. Therefore, DNA extraction strategy and 16S rDNA hypervariable regions both influenced the results of oral microbiota biodiversity profiling, thus should be carefully considered in study design and data interpretation.
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Project description:BackgroundUsefulness of next-generation sequencing (NGS) in assessing bacteria associated with oral squamous cell carcinoma (OSCC) has been undermined by inability to classify reads to the species level.ObjectiveThe purpose of this study was to develop a robust algorithm for species-level classification of NGS reads from oral samples and to pilot test it for profiling bacteria within OSCC tissues.MethodsBacterial 16S V1-V3 libraries were prepared from three OSCC DNA samples and sequenced using 454's FLX chemistry. High-quality, well-aligned, and non-chimeric reads ≥350 bp were classified using a novel, multi-stage algorithm that involves matching reads to reference sequences in revised versions of the Human Oral Microbiome Database (HOMD), HOMD extended (HOMDEXT), and Greengene Gold (GGG) at alignment coverage and percentage identity ≥98%, followed by assignment to species level based on top hit reference sequences. Priority was given to hits in HOMD, then HOMDEXT and finally GGG. Unmatched reads were subject to operational taxonomic unit analysis.ResultsNearly, 92.8% of the reads were matched to updated-HOMD 13.2, 1.83% to trusted-HOMDEXT, and 1.36% to modified-GGG. Of all matched reads, 99.6% were classified to species level. A total of 228 species-level taxa were identified, representing 11 phyla; the most abundant were Proteobacteria, Bacteroidetes, Firmicutes, Fusobacteria, and Actinobacteria. Thirty-five species-level taxa were detected in all samples. On average, Prevotella oris, Neisseria flava, Neisseria flavescens/subflava, Fusobacterium nucleatum ss polymorphum, Aggregatibacter segnis, Streptococcus mitis, and Fusobacterium periodontium were the most abundant. Bacteroides fragilis, a species rarely isolated from the oral cavity, was detected in two samples.ConclusionThis multi-stage algorithm maximizes the fraction of reads classified to the species level while ensuring reliable classification by giving priority to the human, oral reference set. Applying the algorithm to OSCC samples revealed high diversity. In addition to oral taxa, a number of human, non-oral taxa were also identified, some of which are rarely detected in the oral cavity.
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