Dataset Information

16S Based Microbiome Analysis from Healthy Subjects' Skin Swabs Stored for Different Storage Periods Reveal Phylum to Genus Level Changes.

ABSTRACT: Microbiome research and improvements in high throughput sequencing technologies revolutionize our current scientific viewpoint. The human associated microbiome is a prominent focus of clinical research. Large cohort studies are often required to investigate the human microbiome composition and its changes in a multitude of human diseases. Reproducible analyses of large cohort samples require standardized protocols in study design, sampling, storage, processing, and data analysis. In particular, the effect of sample storage on actual results is critical for reproducibility. So far, the effect of storage conditions on the results of microbial analysis has been examined for only a few human biological materials (e.g., stool samples). There is a lack of data and information on appropriate storage conditions on other human derived samples, such as skin. Here, we analyzed skin swab samples collected from three different body locations (forearm, V of the chest and back) of eight healthy volunteers. The skin swabs were soaked in sterile buffer and total DNA was isolated after freezing at -80°C for 24 h, 90 or 365 days. Hypervariable regions V1-2 were amplified from total DNA and libraries were sequenced on an Illumina MiSeq desktop sequencer in paired end mode. Data were analyzed using Qiime 1.9.1. Summarizing all body locations per time point, we found no significant differences in alpha diversity and multivariate community analysis among the three time points. Considering body locations separately significant differences in the richness of forearm samples were found between d0 vs. d90 and d90 vs. d365. Significant differences in the relative abundance of major skin genera (Propionibacterium, Streptococcus, Bacteroides, Corynebacterium, and Staphylococcus) were detected in our samples in Bacteroides only among all time points in forearm samples and between d0 vs. d90 and d90 vs. d365 in V of the chest and back samples. Accordingly, significant differences were detected in the ratios of the main phyla Actinobacteria, Firmicutes, and Bacteroidetes: Actinobacteria vs. Bacteroidetes at d0 vs. d90 (p-value = 0.0234), at d0 vs. d365 (p-value = 0.0234) and d90 vs. d365 (p-value = 0.0234) in forearm samples and at d90 vs. d365 in V of the chest (p-value = 0.0234) and back samples (p-value = 0.0234). The ratios of Firmicutes vs. Bacteroidetes showed no significant changes in any of the body locations as well as the ratios of Actinobacteria vs. Firmicutes at any time point. Studies with larger sample sizes are required to verify our results and determine long term storage effects with regard to specific biological questions.

SUBMITTER: Klymiuk I

PROVIDER: S-EPMC5167739 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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16S Based Microbiome Analysis from Healthy Subjects' Skin Swabs Stored for Different Storage Periods Reveal Phylum to Genus Level Changes.

Klymiuk Ingeborg I Bambach Isabella I Patra Vijaykumar V Trajanoski Slave S Wolf Peter P

Frontiers in microbiology 20161220

Microbiome research and improvements in high throughput sequencing technologies revolutionize our current scientific viewpoint. The human associated microbiome is a prominent focus of clinical research. Large cohort studies are often required to investigate the human microbiome composition and its changes in a multitude of human diseases. Reproducible analyses of large cohort samples require standardized protocols in study design, sampling, storage, processing, and data analysis. In particular, ...[more]

PMID: 28066342

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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.

Project description:Gut dysbiosis is heavily involved in the development of various human diseases. There are thousands of publications per year for investigating the role of gut microbiota in diseases. However, emerging evidence has indicated the frequent data inconsistency between different studies, which is largely overlooked. There are many factors that can cause data variation and inconsistency during the process of microbiota study, in particular, sample storage conditions and sequencing process. Here, we systemically evaluated the impacts of six fecal sample storage conditions (three non-commercial storage protocols, -80°C, -80°C with 70% ethanol (ET_-80°C), 4°C with 70% ethanol (ET_4°C), and three commercial storage reagents, OMNIgeneGUT OMR-200 (GT) and MGIEasy (MGIE) at room temperature, and Longsee at 4°C (LS) on gut microbiome profile based on 16S rRNA gene sequencing. In addition, we also investigated the impacts of storage periods (1 and 2 weeks, or 6 months) and sequencing platform on microbiome profile. The efficacy of storage conditions was evaluated by DNA yield and quality, α and β diversity, relative abundance of the dominant and functional bacteria associated with short-chain fatty acid (SCFA) production, and BAs metabolism. Our current study suggested that -80°C was acceptable for fecal sample storage, and the addition of 70% ethanol had some benefits in maintaining the microbial community structure. Meanwhile, we found that samples in ET_4°C and GT reagents were comparable, both of them introduced some biases in α or β diversity, and the relative abundance of functional bacteria. Samples stored in MGIE reagent resulted in the least variation, whereas the most obvious variations were introduced by LS reagents. In addition, our results indicated that variations caused by storage condition were larger than that of storage time and sequencing platform. Collectively, our study provided a multi-dimensional evaluation on the impacts of storage conditions, storage time periods, and sequencing platform on gut microbial profile.

Dataset Information

16S Based Microbiome Analysis from Healthy Subjects' Skin Swabs Stored for Different Storage Periods Reveal Phylum to Genus Level Changes.

Publications

16S Based Microbiome Analysis from Healthy Subjects' Skin Swabs Stored for Different Storage Periods Reveal Phylum to Genus Level Changes.

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