Dataset Information

Collecting Fecal Samples for Microbiome Analyses in Epidemiology Studies.

ABSTRACT: The need to develop valid methods for sampling and analyzing fecal specimens for microbiome studies is increasingly important, especially for large population studies.Some of the most important attributes of any sampling method are reproducibility, stability, and accuracy. We compared seven fecal sampling methods [no additive, RNAlater, 70% ethanol, EDTA, dry swab, and pre/post development fecal occult blood test (FOBT)] using 16S rRNA microbiome profiling in two laboratories. We evaluated nine commonly used microbiome metrics: abundance of three phyla, two alpha-diversities, and four beta-diversities. We determined the technical reproducibility, stability at ambient temperature, and accuracy.Although microbiome profiles showed systematic biases according to sample method and time at ambient temperature, the highest source of variation was between individuals. All collection methods showed high reproducibility. FOBT and RNAlater resulted in the highest stability without freezing for 4 days. In comparison with no-additive samples, swab, FOBT, and 70% ethanol exhibited the greatest accuracy when immediately frozen.Overall, optimal stability and reproducibility were achieved using FOBT, making this a reasonable sample collection method for 16S analysis.Having standardized method of collecting and storing stable fecal samples will allow future investigations into the role of gut microbiota in chronic disease etiology in large population studies.

SUBMITTER: Sinha R

PROVIDER: S-EPMC4821594 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature

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Collecting Fecal Samples for Microbiome Analyses in Epidemiology Studies.

Sinha Rashmi R Chen Jun J Amir Amnon A Vogtmann Emily E Shi Jianxin J Inman Kristin S KS Flores Roberto R Sampson Joshua J Knight Rob R Chia Nicholas N

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 20151124 2

<h4>Background</h4>The need to develop valid methods for sampling and analyzing fecal specimens for microbiome studies is increasingly important, especially for large population studies.<h4>Methods</h4>Some of the most important attributes of any sampling method are reproducibility, stability, and accuracy. We compared seven fecal sampling methods [no additive, RNAlater, 70% ethanol, EDTA, dry swab, and pre/post development fecal occult blood test (FOBT)] using 16S rRNA microbiome profiling in t ...[more]

PMID: 26604270

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Project description:Few previous studies have assessed stability and "gold-standard" concordance of fecal sample collection methods for whole-genome shotgun metagenomic sequencing (WGSS), an increasingly popular method for studying the gut microbiome. We used WGSS data to investigate ambient temperature stability and putative gold-standard concordance of microbial profiles in fecal samples collected and stored using fecal occult blood test (FOBT) cards, fecal immunochemical test (FIT) tubes, 95% ethanol, or RNAlater. Among 15 Mayo Clinic employees, for each collection method, we calculated intraclass correlation coefficients (ICCs) to estimate stability of fecal microbial profiles after storage for 4?days at ambient temperature and concordance with immediately frozen, no-solution samples (i.e., the putative gold standard). ICCs were estimated for multiple metrics, including relative abundances of select phyla, species, KEGG k-genes (representing any coding sequence that had >70% identity and >70% query coverage with respect to a known KEGG ortholog), KEGG modules, and KEGG pathways; species and k-gene alpha diversity; and Bray-Curtis and Jaccard species beta diversity. ICCs for microbial profile stability were excellent (?90%) for fecal samples collected via most of the collection methods, except those preserved in 95% ethanol. Concordance with the immediately frozen, no-solution samples varied for all collection methods, but the number of observed species and the beta diversity metrics tended to have higher concordance than other metrics. Our findings, taken together with previous studies and feasibility considerations, indicated that FOBT cards, FIT tubes, and RNAlater are acceptable choices for fecal sample collection methods in future WGSS studies.IMPORTANCE A major direction for future microbiome research is implementation of fecal sample collections in large-scale, prospective epidemiologic studies. Studying microbiome-disease associations likely requires microbial data to be pooled from multiple studies. Our findings suggest collection methods that are most optimal to be used standardly across future WGSS microbiome studies.

Project description:Microbiome studies are becoming larger in size to detect the potentially small effect that environmental factors have on our gut microbiomes, or that the microbiome has on our health. Therefore, fast and reproducible DNA isolation methods are needed to handle thousands of fecal samples. We used the Chemagic 360 chemistry and Magnetic Separation Module I (MSMI) instrument to compare two sample preservatives and four different pre-treatment protocols to find an optimal method for DNA isolation from thousands of fecal samples. The pre-treatments included bead beating, sample handling in tube and plate format, and proteinase K incubation. The optimal method offers a sufficient yield of high-quality DNA without contamination. Three human fecal samples (adult, senior, and infant) with technical replicates were extracted. The extraction included negative controls (OMNIgeneGUT, DNA/RNA shield fluid, and Chemagic Lysis Buffer 1) to detect cross-contamination and ZymoBIOMICS Gut Microbiome Standard as a positive control to mimic the human gut microbiome and assess sensitivity of the extraction method. All samples were extracted using Chemagic DNA Stool 200 H96 kit (PerkinElmer, Finland). The samples were collected in two preservatives, OMNIgeneGUT and DNA/RNA shield fluid. DNA quantity was measured using Qubit-fluorometer, DNA purity and quality using gel electrophoresis, and taxonomic signatures with 16S rRNA gene-based sequencing with V3V4 and V4 regions. Bead beating increased bacterial diversity. The largest increase was detected in gram-positive genera Blautia, Bifidobacterium, and Ruminococcus. Preservatives showed minor differences in bacterial abundances. The profiles between the V3V4 and V4 regions differed considerably with lower diversity samples. Negative controls showed signs from genera abundant in fecal samples. Technical replicates of the Gut Standard and stool samples showed low variation. The selected isolation protocol included recommended steps from manufacturer as well as bead beating. Bead beating was found to be necessary to detect hard-to-lyse bacteria. The protocol was reproducible in terms of DNA yield among different stool replicates and the ZymoBIOMICS Gut Microbiome Standard. The MSM1 instrument and pre-treatment in a 96-format offered the possibility of automation and handling of large sample collections. Both preservatives were feasible in terms of sample handling and had low variation in taxonomic signatures. The 16S rRNA target region had a high impact on the composition of the bacterial profile.ImportanceNext-generation sequencing (NGS) is a widely used method for determining the composition of the gut microbiota. Due to the differences in the gut microbiota composition between individuals, microbiome studies have expanded into large population studies to maximize detection of small effects on microbe-host interactions. Thus, the demand for a rapid and reliable microbial profiling is continuously increasing, making the optimization of high-throughput 96-format DNA extraction integral for NGS-based downstream applications. However, experimental protocols are prone to bias and errors from sample collection and storage, to DNA extraction, primer selection and sequencing, and bioinformatics analyses. Methodological bias can contribute to differences in microbiome profiles, causing variability across studies and laboratories using different protocols. To improve consistency and confidence of the measurements, the standardization of microbiome analysis methods has been recognized in many fields.

Project description:Advances have been made to standardize 16S rRNA gene amplicon based studies for inter-study comparisons, yet there are many opportunities for systematic error that may render these comparisons improper and misleading. The fecal microbiome of horses has been examined previously, however, no universal horse fecal collection method and sample processing procedure has been established. This study was initialized in large part to ensure that samples collected by different individuals from different geographical areas (i.e., crowdsourced) were not contaminated due to less than optimal sampling or holding conditions. In this study, we examined the effect of sampling the surface of fecal pellets compared to homogenized fecal pellets, and also the effect of time of sampling after defecation on 'bloom' taxa (bloom taxa refers to microbial taxa that can grow rapidly in horse feces post-defecation) using v4 16S rRNA amplicon libraries. A total of 1,440,171 sequences were recovered from 65 horse fecal samples yielding a total of 3,422 OTUs at 97% similarity. Sampling from either surface or homogenized feces had no effect on diversity and little effect on microbial composition. Sampling at various time points (0, 2, 4, 6, 12 h) had a significant effect on both diversity and community composition of fecal samples. Alpha diversity (Shannon index) initially increased with time as regrowth taxa were detected in the amplicon libraries, but by 12 h the diversity sharply decreased as the community composition became dominated by a few bloom families, including Bacillaceae, Planococcaeae, and Enterococcaceae, and other families to a lesser extent. The results show that immediate sampling of horse feces must be done in order to ensure accurate representation of horse fecal samples. Also, several of the bloom taxa found in this study are known to occur in human and cattle feces post defecation. The dominance of these taxa in feces shortly after defecation suggests that the feces is an important habitat for these organisms, and horse fecal samples that were improperly stored can be identified by presence of bloom taxa.

Project description:Background: Integrated microbiome and metabolomics analyses hold the potential to reveal interactions between host and microbiota in relation to disease risks. However, there are few studies evaluating how field methods influence fecal microbiome characterization and metabolomics profiling. Methods: Five fecal collection methods [immediate freezing at -20°C without preservative, OMNIgene GUT, 95% ethanol, RNAlater, and Flinders Technology Associates (FTA) cards] were used to collect 40 fecal samples from eight healthy volunteers. We performed gut microbiota 16S rRNA sequencing, untargeted metabolomics profiling, and targeted metabolomics focusing on short chained fatty acids (SCFAs). Metrics included α-diversity and β-diversity as well as distributions of predominant phyla. To evaluate the concordance with the "gold standard" immediate freezing, the intraclass correlation coefficients (ICCs) for alternate fecal collection systems were calculated. Correlations between SCFAs and gut microbiota were also examined. Results: The FTA cards had the highest ICCs compared to the immediate freezing method for α-diversity indices (ICCs = 0.96, 0.96, 0.76 for Shannon index, Simpson's Index, Chao-1 Index, respectively), followed by OMNIgene GUT, RNAlater, and 95% ethanol. High ICCs (all >0.88) were observed for all methods for the β-diversity metric. For untargeted metabolomics, in comparison to immediate freezing which detected 621 metabolites at ≥75% detectability level, 95% ethanol showed the largest overlapping set of metabolites (n = 430; 69.2%), followed by FTA cards (n = 330; 53.1%) and OMNIgene GUT (n = 213; 34.3%). Both OMNIgene GUT (ICCs = 0.82, 0.93, 0.64) and FTA cards (ICCs = 0.87, 0.85, 0.54) had acceptable ICCs for the top three predominant SCFAs (butyric acid, propionic acid and acetic acid). Nominally significant correlations between bacterial genera and SCFAs (P < 0.05) were observed in fecal samples collected by different methods. Of note, a high correlation between the genus Blautia (known butyrate producer) and butyric acid was observed for both immediate freezing (r = 0.83) and FTA cards (r = 0.74). Conclusions: Four alternative fecal collection methods are generally comparable with immediate freezing, but there are differences in certain measures of the gut microbiome and fecal metabolome across methods. Choice of method depends on the research interests, simplicity of fecal collection procedures and ease of transportation to the lab, especially for large epidemiological studies.

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Collecting Fecal Samples for Microbiome Analyses in Epidemiology Studies.

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Collecting Fecal Samples for Microbiome Analyses in Epidemiology Studies.

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