Mock Microbiome
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB20952 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR1988958.fastq.gz | Fastqsanger.gz |
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Project description:Benchmarking of metagenomics pipelines
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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.
2019-03-29 | PXD006033 | Pride
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.
2017-05-12 | PXD006118 | Pride
Project description:Aging is associated with declining immunity and inflammation as well as alterations in the gut microbiome with a decrease of beneficial microbes and increase in pathogenic ones. The aim of this study was to investigate aging associated gut microbiome in relation to immunologic and metabolic profile in a non-human primate (NHP) model. 12 old (age>18 years) and 4 young (age 3-6 years) Rhesus macaques were included in this study. Immune cell subsets were characterized in PBMC by flow cytometry and plasma cytokines levels were determined by bead based multiplex cytokine analysis. Stool samples were collected by ileal loop and investigated for microbiome analysis by shotgun metagenomics. Serum, gut microbial lysate and microbe-free fecal extract were subjected to metabolomic analysis by mass-spectrometry. Our results showed that the old animals exhibited higher inflammatory biomarkers in plasma and lower CD4 T cells with altered distribution of naïve and memory T cell maturation subsets. The gut microbiome in old animals had higher abundance of Archaeal and Proteobacterial species and lower Firmicutes than the young. Significant enrichment of metabolites that contribute to inflammatory and cytotoxic pathways was observed in serum and feces of old animals compared to the young. We conclude that aging NHP undergo immunosenescence and age associated alterations in the gut microbiome that has a distinct metabolic profile.
2022-02-01 | E-MTAB-10160 | biostudies-arrayexpress
Project description:ATAC-seq is a frequently used assay to study chromatin accessibility levels. Differential chromatin accessibility level analyses between biological groups and functional interpretation of these differential regions are essential in ATAC-seq data analyses. Although distinct methods and analyses pipelines are developed for this purpose, we are missing a stand-along R package that combines state-of-the art differential analyses and functional enrichment analyses. To fill this gap, we developed cinaR, which is a single wrapper function and provides users with various configurable plots. To show-case this pipeline we provide these bulk ATAC-seq samples from bone-marrow of 3 & 18 months old New Zelland Obese (NZO) mice and show the activation of pro-inflammatory pathways.
2021-01-20 | GSE165120 | GEO
Project description:Toward standards in clinical microbiome studies: comparison of DNA extraction methods and bioinformatic pipelines
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Project description:Abstract To quantify the biases introduced during human gut microbiome studies, analyzing an artificial mock community as the reference microbiome is indispensable. However, there are still limited resources for a mock community which well represents the human gut microbiome. Here, we constructed a novel mock community comprising the type strains of 18 major bacterial species in the human gut and assessed the influence of experimental and bioinformatics procedures on the 16S rRNA gene and shotgun metagenomic sequencing. We found that DNA extraction methods greatly affected the DNA yields and taxonomic composition of sequenced reads, and that some of the commonly used primers for 16S rRNA genes were prone to underestimate the abundance of some gut commensal taxa such as Erysipelotrichia, Verrucomicrobiota and Methanobacteriota. Binning of the assembled contigs of shotgun metagenomic sequences by MetaBAT2 produced phylogenetically consistent, less-contaminated bins with varied completeness. The ensemble approach of multiple binning tools by MetaWRAP can improve completeness but sometimes increases the contamination rate. Our benchmark study provides an important foundation for the interpretation of human gut microbiome data by providing means for standardization among gut microbiome data obtained with different methodologies and will facilitate further development of analytical methods.
| S-EPMC10229288 | biostudies-literature
Project description:We performed a deep, comparative metaproteomics study on three aerobic granular sludge wastewater treatment communities to determine the core microbiome and the occurrence and relative abundance of the central nutrient-removing organisms. Our systematic study underscores the importance of metaproteomics when characterizing complex microbiomes, and the necessity of accurate reference sequence databases to improve the comparison between studies and omics approaches.
2023-11-19 | PXD030677 | Pride