16s rrna

In this work, we compare the resolution of V2-V3 and V3-V4 16S rRNA regions for the purposes of estimating microbial community diversity using paired-end Illumina MiSeq reads, and show that the fragment, including V2 and V3 regions, has higher resolution for lower-rank taxa (genera and species). It allows for a more precise distance-based clustering of reads into species-level OTUs. Statistically convergent estimates of the diversity of major species (defined as those that together are covered by 95% of reads) can be achieved at the sample sizes of 10000 to 15000 reads. The relative error of the Shannon index estimate for this condition is lower than 4%. Design Type(s) sequence analysis objective • biodiversity assessment objective Measurement Type(s) rRNA_16S Technology Type(s) DNA sequencing assay Factor Type(s) aquatic natural environment • sequence_variant Sample Characteristic(s) soil metagenome • freshwater metagenome • Lake Baikal • lake sediment • oil seep • mud volcano Modern microbiome studies often rely on the analysis of 16S ribosomal RNA sequences for the taxonomic identification of bacterial and archaeal strains de facto standard for prokaryotic taxonomy. The 16S rRNA gene is approximately 1600 base pairs long and includes nine hypervariable regions of varying conservation (V1-V9) Metabarcoding using 16S rRNA marker is widespread in the studies of various microbial communities Earlier metabarcoding works were performed using 454 Life Sciences sequencer i.e., ...

In …for investigating evolutionary relatedness is 16S rRNA, a sequence of DNA that encodes the RNA component of the smaller subunit of the bacterial ribosome. The 16S rRNA gene is present in all bacteria, and a related form occurs in all cells, including those of eukaryotes. Analysis of the 16S rRNA… taxonomy of bacteria •

The gut microbiota is associated with the health and longevity of the host. A few methods, such as fecal microbiota transplantation and oral administration of probiotics, have been applied to alter the gut microbiome and promote healthy aging. The changes in host microbiomes still remain poorly understood. Here, we characterized both the changes in gut microbial communities and their functional potential derived from colon samples in mouse models during aging. We achieved this through four procedures including co-housing, serum injection, parabiosis, and oral administration of Akkermansia muciniphila as probiotics using bacterial 16 S rRNA sequencing and shotgun metagenomic sequencing. The dataset comprised 16 S rRNA sequencing (36,249,200 paired-end reads, 107 sequencing data) and metagenomic sequencing data (307,194,369 paired-end reads, 109 sequencing data), characterizing the taxonomy of bacterial communities and their functional potential during aging and rejuvenation. The generated data expand the resources of the gut microbiome related to aging and rejuvenation and provide a useful dataset for research on developing therapeutic strategies to achieve healthy active aging. Measurement(s) Microbiome Technology Type(s) Metagenome • Bacterial 16 S RNA Factor Type(s) Ageing • Co-housing • Parabiosis • Serum-injection • Akkermansia (AK) treatment Sample Characteristic - Organism Mus musculus Sample Characteristic - Environment animal cage Sample Characteristic - Location S...

In …for investigating evolutionary relatedness is 16S rRNA, a sequence of DNA that encodes the RNA component of the smaller subunit of the bacterial ribosome. The 16S rRNA gene is present in all bacteria, and a related form occurs in all cells, including those of eukaryotes. Analysis of the 16S rRNA… taxonomy of bacteria •

The gut microbiota is associated with the health and longevity of the host. A few methods, such as fecal microbiota transplantation and oral administration of probiotics, have been applied to alter the gut microbiome and promote healthy aging. The changes in host microbiomes still remain poorly understood. Here, we characterized both the changes in gut microbial communities and their functional potential derived from colon samples in mouse models during aging. We achieved this through four procedures including co-housing, serum injection, parabiosis, and oral administration of Akkermansia muciniphila as probiotics using bacterial 16 S rRNA sequencing and shotgun metagenomic sequencing. The dataset comprised 16 S rRNA sequencing (36,249,200 paired-end reads, 107 sequencing data) and metagenomic sequencing data (307,194,369 paired-end reads, 109 sequencing data), characterizing the taxonomy of bacterial communities and their functional potential during aging and rejuvenation. The generated data expand the resources of the gut microbiome related to aging and rejuvenation and provide a useful dataset for research on developing therapeutic strategies to achieve healthy active aging. Measurement(s) Microbiome Technology Type(s) Metagenome • Bacterial 16 S RNA Factor Type(s) Ageing • Co-housing • Parabiosis • Serum-injection • Akkermansia (AK) treatment Sample Characteristic - Organism Mus musculus Sample Characteristic - Environment animal cage Sample Characteristic - Location S...

In this work, we compare the resolution of V2-V3 and V3-V4 16S rRNA regions for the purposes of estimating microbial community diversity using paired-end Illumina MiSeq reads, and show that the fragment, including V2 and V3 regions, has higher resolution for lower-rank taxa (genera and species). It allows for a more precise distance-based clustering of reads into species-level OTUs. Statistically convergent estimates of the diversity of major species (defined as those that together are covered by 95% of reads) can be achieved at the sample sizes of 10000 to 15000 reads. The relative error of the Shannon index estimate for this condition is lower than 4%. Design Type(s) sequence analysis objective • biodiversity assessment objective Measurement Type(s) rRNA_16S Technology Type(s) DNA sequencing assay Factor Type(s) aquatic natural environment • sequence_variant Sample Characteristic(s) soil metagenome • freshwater metagenome • Lake Baikal • lake sediment • oil seep • mud volcano Modern microbiome studies often rely on the analysis of 16S ribosomal RNA sequences for the taxonomic identification of bacterial and archaeal strains de facto standard for prokaryotic taxonomy. The 16S rRNA gene is approximately 1600 base pairs long and includes nine hypervariable regions of varying conservation (V1-V9) Metabarcoding using 16S rRNA marker is widespread in the studies of various microbial communities Earlier metabarcoding works were performed using 454 Life Sciences sequencer i.e., ...