Impact of storage on human stool microbiome
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB32925 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR3360150_1.fastq.gz | Fastqsanger.gz | |||
| ERR3360150_2.fastq.gz | Fastqsanger.gz | |||
| ERR3360160_1.fastq.gz | Fastqsanger.gz | |||
| ERR3360160_2.fastq.gz | Fastqsanger.gz | |||
| ERR3360170_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 178 |
Similar Datasets
Project description:With the technological advances of the last decade, it is now feasible to analyze environmental samples of vast complexity, such as human stool specimen, using meta-omics techniques like metaproteomics. Still the most sophisticated, sensitive instruments can only extract information that a sample contains in the first place. This highlights the need for initial sample preparation to preserve as much unaltered information as possible. Yet little is known about the effects different processing approaches have on the final analysis results. This study analyzes human stool samples applying metaproteomics and shows that the initial sample storage has a massive effect on the taxonomic composition of proteins identified. The findings are backed up by the results of the metagenomics analysis of the same samples. This suggests, that great care should be taken in choosing storage conditions for (omics) studies, as well as in comparing the results of experiments with different initial processing.
2019-09-26 | PXD014482 | Pride
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.
| 2255499 | ecrin-mdr-crc
Project description:<p><strong>BACKGROUND:</strong> Stool metabolites provide essential insights into the function of the gut microbiome. The current gold standard for storage of stool samples for metabolomics is flash-freezing at - 80 °C which can be inconvenient and expensive. Ambient temperature storage of stool is more practical, however no available methodologies adequately preserve the metabolomic profile of stool. A novel sampling kit (OMNImet.GUT; DNA Genotek, Inc.) was introduced for ambient temperature storage and stabilization of feces for metabolomics; we aimed to test the performance of this kit vs flash-freezing. To do this stool was collected from an infant's diaper was divided into 2 aliquots: 1) flash-frozen and 2) stored in an OMNImet.GUT tube at ambient temperature for 3-4 days. Samples from the same infant were collected at 2 different timepoints to assess metabolite changes over time. Subsequently, all samples underwent metabolomic analysis by liquid chromatography-tandem mass spectrometry (LC-MS/MS).</p><p><strong>RESULTS:</strong> Paired fecal samples (flash-frozen and ambient temperature) from 16 infants were collected at 2 timepoints (32 individual samples, 64 aliquots). Similar numbers of metabolites were detected in both the frozen and ambient temperature samples (1126 in frozen, 1107 in ambient temperature, 1064 shared between sample types). Metabolite abundances were strongly correlated between storage methods (median Spearman correlation Rs = 0.785 across metabolites). Hierarchical clustering analysis and principal component analysis showed that samples from the same individuals at a given timepoint clustered closely, regardless of the storage method. Repeat samples from the same individual were compared by paired t-test, separately for the frozen and OMNImet.GUT. The number of metabolites in each biochemical class that significantly changed (p < 0.05) at timepoint 2 relative to timepoint 1 was similar in flash-frozen vs ambient temperature storage. Changes in microbiota modified metabolites over time were also consistent across both methodologies.</p><p><strong>CONCLUSION:</strong> Ambient temperature storage and stabilization of stool in the OMNImet.GUT device yielded comparable metabolomic results to flash freezing in terms of 1) the identity and abundance of detected biochemicals 2) the distinct metabolomic profiles of subjects and 3) changes in metabolites over time that are plausibly microbiota-induced. This method potentially provides a more convenient, less expensive home collection and storage option for stool metabolomic analysis.</p>
2021-01-27 | MTBLS201 | MetaboLights
Project description:<p>We investigate the hypothesis that consistent changes in the human gut microbiome are associated with Crohn's disease, a form of inflammatory bowel disease, and that altered microbiota contributes to pathogenesis. Analysis of this problem is greatly complicated by the fact that multiple factors influence the composition of the gut microbiota, including diet, host genotype, and disease state. For example, data from us and others document a drastic impact of diet on the composition of the gut microbiome. No amount of sequencing will yield a useful picture of the role of the microbiota in disease if samples are confounded with uncontrolled variables.</p> <p>We aim to characterize the composition of the gut microbiome while controlling for diet, host genotype, and disease state. Diet is controlled by analyzing children treated for Crohn's disease by placing them on a standardized elemental diet, and by testing effects of different diets on the gut microbiome composition in adult volunteers. Genotype is analyzed by large scale SNP genotyping, which is already underway and separately funded--team member Hakon Hakonarson is currently genotyping 50 children a week at ~half a million loci each and investigating connections with inflammatory bowel disease. Clinical status is ascertained in the very large IBD practice in the UPenn/CHOP hospital system. Effects of diet, host genotype, and disease state on the gut microbiome are summarized in a multivariate model, allowing connections between microbiome and disease to be assessed free of confounding factors.</p> <p>This project is divided into four sub-studies. In the Fecal Storage Methods (FSM) study, methods of stool storage and DNA extraction are compared to examine their impact on DNA sequence analysis results. The Controlled Feeding Experiment (CaFE) addresses the effects of controlled diets on the gut microbiome. In the Cross-sectional Study of Diet and Stool Microbiome Composition (COMBO), the effects of diet analyzed using surveys and deep sequencing of stool specimens. The fourth study, Pediatric Longitudinal Study of Elemental Diet and Stool Microbiome Composition (PLEASE), examines the effects of an elemental diet treatment on pediatric patients diagnosed with inflammatory bowel disease (IBD), particularly Crohn's disease.</p> <p> <ul> <li>Fecal Storage Methods (FSM): Cross-sectional study</li> <li>Controlled Feeding Experiment (CaFE): Controlled trial</li> <li>Cross-sectional Study of Diet and Stool Microbiome Composition (COMBO): Cross-sectional study</li> <li>Pediatric Longitudinal Study of Elemental Diet and Stool Microbiome Composition (PLEASE): Longitudinal cohort study</li> </ul> </p>
| phs000252 | dbGaP
Project description:Dysbiotic configurations of the human gut microbiota have been linked with colorectal cancer (CRC). Human small non-coding RNAs are also implicated in CRC and recent findings suggest that their release in the gut lumen contributes to shape the gut microbiota. Bacterial small RNAs (bsRNAs) may also play a role in carcinogenesis but their role is less explored. Here, we performed small RNA and shotgun sequencing on 80 stool specimens of patients with CRC, or adenomas, and healthy subjects collected in a cross-sectional study to evaluate their combined use as a predictive tool for disease detection. We reported a considerable overlap and correlation between metagenomic and bsRNA quantitative taxonomic profiles obtained from the two approaches. Furthermore, we identified a combined predictive signature composed by 32 features from human and microbial small RNAs and DNA-based microbiome able to accurately classify CRC from healthy and adenoma samples (AUC= 0.87). In summary we reported evidence that host-microbiome dysbiosis in CRC can be observed also by altered small RNA stool profiles. Integrated analyses of the microbiome and small RNAs in the human stool may provide insights for designing more accurate tools for diagnostic purposes.
2019-08-30 | GSE132236 | GEO
Project description:impact of stool sample logistics on metabolites and microbial composition
| PRJEB71694 | ENA
Project description:Mouse stool microbiome Raw sequence reads
| PRJNA726993 | ENA
Project description:mouse stool microbiome Raw sequence reads
| PRJNA737149 | ENA
Project description:BackgroundMultiple factors can influence stool sample integrity upon sample collection. Preservation of faecal samples for microbiome studies is therefore an important step, particularly in tropical regions where resources are limited and high temperatures may significantly influence microbiota profiles. Freezing is the accepted standard to preserve faecal samples however, cold chain methods are often unfeasible in fieldwork scenarios particularly in low and middle-income countries and alternatives are required. This study therefore aimed to address the impact of different preservative methods, time-to-freezing at ambient tropical temperatures, and stool heterogeneity on stool microbiome diversity and composition under real-life physical environments found in resource-limited fieldwork conditions.MethodsInner and outer stool samples collected from one specimen obtained from three children were stored using different storage preservation methods (raw, ethanol and RNAlater) in a Ugandan field setting. Mixed stool was also stored using these techniques and frozen at different time-to-freezing intervals post-collection from 0-32 h. Metataxonomic profiling was used to profile samples, targeting the V1-V2 regions of 16S rRNA with samples run on a MiSeq platform. Reads were trimmed, combined and aligned to the Greengenes database. Microbial diversity and composition data were generated and analysed using Quantitative Insights Into Microbial Ecology and R software.ResultsChild donor was the greatest predictor of microbiome variation between the stool samples, with all samples remaining identifiable to their child of origin despite the stool being stored under a variety of conditions. However, significant differences were observed in composition and diversity between preservation techniques, but intra-preservation technique variation was minimal for all preservation methods, and across the time-to-freezing range (0-32 h) used. Stool heterogeneity yielded no apparent microbiome differences.ConclusionsStool collected in a fieldwork setting for comparative microbiome analyses should ideally be stored as consistently as possible using the same preservation method throughout.
| S-EPMC6894433 | biostudies-literature
Project description:Primary outcome(s): Analysis of the diversity and composition of the gut microbiome by 16S rRNA sequencing
Study Design: Observational Study Model : Others, Time Perspective : Prospective, Enrollment : 60, Biospecimen Retention : Collect & Archive- Sample with DNA, Biospecimen Description : Blood, Stool
| 26030 | ecrin-mdr-crc