Project description:We examined 36 biopsies taken from digital dermatitis lesions of Holstein cows. The target was the V3 -V4 variable region of 16S rRNA using Treponema specific primers. We identified 20 different taxa of Treponema using this approach. Phylogenetic study of the Treponema taxa found in digital dermatitis lesions of Holstein cows.
Project description:We examined 36 biopsies taken from digital dermatitis lesions of Holstein cows. The target was the V3 -V4 variable region of 16S rRNA using Treponema specific primers. We identified 20 different taxa of Treponema using this approach.
Project description:The objectives of this study were to establish a microbiome profile for oral epithelial dysplasia using archival lesion swab samples to characterize the community variations and the functional potential of the microbiome using 16S rRNA gene sequencing
Project description:A phylogenetic microarray targeting 66 families described in the human gut microbiota has been developped aud used to monitor the gut microbiota's structure and diversity. The microarray format provided by Agilent and used in this study is 8x15K. A study with a total of 4 chips was realized. Arrays 1 and 2: Hybridization with 100ng of labelled 16S rRNA gene amplicons from a mock community sample and 250ng of labelled 16S rRNA gene amplicons from 1 faecal sample. Each Agilent-030618 array probe (4441) was synthetized in three replicates. Arrays 3 and 4: Hybridization with 250ng of labelled 16S rRNA gene amplicons from 2 faecal samples. Each Agilent-40558 array probe (4441) was synthetized in three replicates.
Project description:The impact of mono-chronic S. stercoralis infection on the gut microbiome and microbial activities in infected participants was explored. The 16S rRNA gene sequencing of a longitudinal study with 2 sets of human fecal was investigated. Set A, 42 samples were matched, and divided equally into positive (Pos) and negative (Neg) for S. stercoralis diagnoses. Set B, 20 samples of the same participant in before (Ss+PreT) and after (Ss+PostT) treatment was subjected for 16S rRNA sequences and LC-MS/MS to explore the effect of anti-helminthic treatment on microbiome proteomes.
Project description:Gas hydrates, also known as clathrates, are cages of ice-like water crystals encasing gas molecules such as methane (CH4). Despite the global importance of gas hydrates, their microbiomes remain mysterious. Microbial cells are physically associated with hydrates, and the taxonomy of these hydrate-associated microbiomes is distinct from non-hydrate-bearing sites. Global 16S rRNA gene surveys show that members of sub-clade JS-1 of the uncultivated bacterial candidate phylum Atribacteria are the dominant taxa in gas hydrates. The Atribacteria phylogeny is highly diverse, suggesting the potential for wide functional variation and niche specialization. Here, we examined the distribution, phylogeny, and metabolic potential of uncultivated Atribacteria in cold, salty, and high-pressure sediments beneath Hydrate Ridge, off the coast of Oregon, USA, using a combination of 16S rRNA gene amplicon, metagenomic, and metaproteomic analysis. Methods were developed to extract bacterial cellular protein from these sediments, as outlined below. Sample Description Three sediments samples were collected from beneath Hydrate Ridge, off the coast of Oregon, USA. Sediments were cored at ODP site 1244 (44°35.1784´N; 125°7.1902´W; 895 m water depth) on the eastern flank of Hydrate Ridge ~3 km northeast of the southern summit on ODP Leg 204 in 2002 and stored at -80°C at the IODP Gulf Coast Repository. E10H5 sediment is from 68.5 meters below sediment surface interface C1H2 sediment is from 2 meters below sediment surface interface. C3H4 sediment is from 21 meters below sediment surface interface.
Project description:Gut microbiota were assessed in 540 colonoscopy-screened adults by 16S rRNA gene sequencing of stool samples. Investigators compared gut microbiota diversity, overall composition, and normalized taxon abundance among these groups.
Project description:In this study, we performed a comparative analysis of gut microbiota composition and gut microbiome-derived bacterial extracellular vesicles (bEVs) isolated from patients with solid tumours and healthy controls. After isolating bEVs from the faeces of solid tumour patients and healthy controls, we performed spectrometry analysis of their proteomes and next-generation sequencing (NGS) of the 16S gene. We also investigated the gut microbiomes of faeces from patientsand controls using 16S rRNA sequencing. Machine learning was used to classify the samples into patients and controls based on their bEVs and faecal microbiomes.
Project description:A metaproteomics analysis was conducted on the infant fecal microbiome to characterize global protein expression in 8 samples obtained from infants with a range of early-life experiences. Samples included breast-, formula- or mixed-fed, mode of delivery, and antibiotic treatment and one set of monozygotic twins. Although label-free mass spectrometry-based proteomics is routinely used for the identification and quantification of thousands of proteins in complex samples, the metaproteomic analysis of the gut microbiome presents particular technical challenges. Among them: the extreme complexity and dynamic range of member taxa/species, the need for matched, well-annotated metagenomics databases, and the high inter-protein sequence redundancy/similarity between related members. In this study, a metaproteomic approach was developed for assessment of the biological phenotype and functioning, as a complement to 16S rRNA sequencing analysis to identify constituent taxa. A sample preparation method was developed for recovery and lysis of bacterial cells, followed by trypsin digestion, and pre-fractionation using Strong Cation Exchange chromatography. Samples were then subjected to high performance LC-MS/MS. Data was searched against the Human Microbiome Project database, and a homology-based meta-clustering strategy was used to combine peptides from multiple species into representative proteins. Bacterial taxonomies were also identified, based on species-specific protein sequences, and protein metaclusters were assigned to pathways and functional groups. The results obtained demonstrate the applicability of this approach for performing qualitative comparisons of human fecal microbiome composition, physiology and metabolism, and also provided a more detailed assessment of microbial composition in comparison to 16S rRNA.
Project description:In this study we developed metaproteomics based methods for quantifying taxonomic composition of microbiomes (microbial communities). We also compared metaproteomics based quantification to other quantification methods, namely metagenomics and 16S rRNA gene amplicon sequencing. The metagenomic and 16S rRNA data can be found in the European Nucleotide Archive (Study number: PRJEB19901). For the method development and comparison of the methods we analyzed three types of mock communities with all three methods. The communities contain between 28 to 32 species and strains of bacteria, archaea, eukaryotes and bacteriophage. For each community type 4 biological replicate communities were generated. All four replicates were analyzed by 16S rRNA sequencing and metaproteomics. Three replicates of each community type were analyzed with metagenomics. The "C" type communities have same cell/phage particle number for all community members (C1 to C4). The "P" type communities have the same protein content for all community members (P1 to P4). The "U" (UNEVEN) type communities cover a large range of protein amounts and cell numbers (U1 to U4). We also generated proteomic data for four pure cultures to test the specificity of the protein inference method. This data is also included in this submission.