Collecting Fecal Samples for Microbiome Analyses in Epidemiology Studies

Quantification of Human Microbiome Stability Over 6 Months: Implications for Epidemiologic Studies

Temporal variation in microbiome measurements can reduce statistical power in research studies. Quantification of this variation is essential for designing studies of chronic disease. We analyzed 16S ribosomal RNA profiles in paired biological specimens separated by 6 months from 3 studies conducted during 1985-2013 (a National Cancer Institute colorectal cancer study, a Costa Rica study, and the Human Microbiome Project). We evaluated temporal stability by calculating intraclass correlation coefficients (ICCs). Sample sizes needed in order to detect microbiome differences between equal numbers of cases and controls for a nested case-control design were calculated on the basis of estimated ICCs. Across body sites, 12 phylum-level ICCs were greater than 0.5. Similarly, 11 alpha-diversity ICCs were greater than 0.5. Fecal beta-diversity estimates had ICCs over 0.5. For a single collection with most microbiome metrics, detecting an odds ratio of 2.0 would require 300-500 cases when matching 1 case to 1 control at P = 0.05. Use of 2 or 3 sequential specimens reduces the number of required subjects by 40%-50% for low-ICC metrics. Relative abundances of major phyla and alpha-diversity metrics have low temporal stability. Thus, detecting associations of moderate effect size with these metrics will require large sample sizes. Because beta diversity for feces is reasonably stable over time, smaller sample sizes can detect associations with community composition. Sequential prediagnostic specimens from thousands of prospectively ascertained cases are required to detect modest disease associations with particular microbiome metrics.

Generalized Hotelling's test for paired compositional data with application to human microbiome studies

The human microbiome is a dynamic system that changes due to diseases, medication, change in diet, etc. The paired design is a common approach to evaluate the microbial changes while controlling for the inherent differences between people. For example, microbiome data may be collected from the same individuals before and after a treatment. Two challenges exist in analyzing this type of data. First, microbiome data are compositional such that the reads for all taxa in each sample are constrained to sum to a constant. Second, the number of taxa can be much larger than the sample size. Few statistical methods exist to analyze such data besides methods that test one taxon at a time. In this paper, we propose to first conduct a log-ratio transformation of the compositions, and then develop a generalized Hotelling's test (GHT) to evaluate whether the average microbiome compositions are equivalent in the paired samples. We replace the sample covariance matrix in standard Hotelling's statistic by a shrinkage-based covariance, calculated as a weighted average of the sample covariance and a positive definite target matrix. The optimal weighting can be obtained for many commonly used target matrices. We develop a permutation procedure to assess the statistical significance. Extensive simulations show that our proposed method has well-controlled type I error and better power than a few ad hoc approaches. We apply our method to examine the vaginal microbiome changes in response to treatments for menopausal hot flashes. An R package " GHT" is freely available at https://github.com/zhaoni153/GHT.

GMPR: A robust normalization method for zero-inflated count data with application to microbiome sequencing data

Normalization is the first critical step in microbiome sequencing data analysis used to account for variable library sizes. Current RNA-Seq based normalization methods that have been adapted for microbiome data fail to consider the unique characteristics of microbiome data, which contain a vast number of zeros due to the physical absence or under-sampling of the microbes. Normalization methods that specifically address the zero-inflation remain largely undeveloped. Here we propose geometric mean of pairwise ratios—a simple but effective normalization method—for zero-inflated sequencing data such as microbiome data. Simulation studies and real datasets analyses demonstrate that the proposed method is more robust than competing methods, leading to more powerful detection of differentially abundant taxa and higher reproducibility of the relative abundances of taxa.

The current state and future direction of DoD gut microbiome research: a summary of the first DoD gut microbiome informational meeting

The gut microbiome is increasingly recognized as integral to human health, and is emerging as a mediator of human physical and cognitive performance. This has led to the recognition that US Department of Defense (DoD) research supporting a healthy and resilient gut microbiome will be critical to optimizing the health and performance of future Warfighters. To facilitate knowledge dissemination and collaboration, identify resource capabilities and gaps, and maximize the positive impact of gut microbiome research on the Warfighter, DoD partners in microbiome research participated in a 2-day informational meeting co-hosted by the Natick Soldier Research, Engineering and Development Center (NSRDEC) and the US Army Research Institute of Environmental Medicine (USARIEM) on 16–17 November 2015. Attendee presentations and discussions demonstrated that multiple DoD organizations are actively advancing gut microbiome research. Common areas of research included the influence of military-relevant stressors on interactions between the microbiome and Warfighter biology, manipulation of the microbiome to influence Warfighter health, and use of the microbiome as a biomarker of Warfighter health status. Although resources and capabilities are available, they vary across laboratories and it was determined that centralizing certain DoD capabilities could accelerate progress. More significantly, the meeting created a foundation for a coordinated gut microbiome and nutrition research program aligning key DoD partners in the area of microbiome research. This report details the presentations and discussions presented during the 1st DoD Gut Microbiome Informational Meeting.

Reproducibility and repeatability of six high-throughput 16S rDNA sequencing protocols for microbiota profiling

Culture-independent molecular techniques and advances in next generation sequencing (NGS) technologies make large-scale epidemiological studies on microbiota feasible. A challenge using NGS is to obtain high reproducibility and repeatability, which is mostly attained through robust amplification. We aimed to assess the reproducibility of saliva microbiota by comparing triplicate samples. The microbiota was produced with simplified in-house 16S amplicon assays taking advantage of large number of barcodes. The assays included primers with Truseq (TS-tailed) or Nextera (NX-tailed) adapters and either with dual index or dual index plus a 6-nt internal index. All amplification protocols produced consistent microbial profiles for the same samples. Although, in our study, reproducibility was highest for the TS-tailed method. Five replicates of a single sample, prepared with the TS-tailed 1-step protocol without internal index sequenced on the HiSeq platform provided high alpha-diversity and low standard deviation (mean Shannon and Inverse Simpson diversity was 3.19 ± 0.097 and 13.56 ± 1.634 respectively). Large-scale profiling of microbiota can consistently be produced by all 16S amplicon assays. The TS-tailed-1S dual index protocol is preferred since it provides repeatable profiles on the HiSeq platform and are less labour intensive.

Optimization of fecal sample processing for microbiome study - The journey from bathroom to bench

Although great interest has been displayed by researchers in the contribution of gut microbiota to human health, there is still no standard protocol with consensus to guarantee the sample quality of metagenomic analysis. Here we reviewed existing methodology studies and present suggestions for optimizing research pipeline from fecal sample collection to DNA extraction. First, we discuss strategies of clinical metadata collection as common confounders for microbiome research. Second, we propose general principles for freshly collected fecal sample and its storage and share a DIY stool collection kit protocol based on the manual procedure of Human Microbiome Project (HMP). Third, we provide a useful information of collection kit with DNA stabilization buffers and compare their pros and cons for multi-omic study. Fourth, we offer technical strategies as well as information of novel tools for sample aliquoting before long-term storage. Fifth, we discuss the substantial impact of different DNA extraction protocols on technical variations of metagenomic analysis. And lastly, we point out the limitation of current methods and the unmet needs for better quality control of metagenomic analysis. We hope the information provided here will help investigators in this exciting field to advance their studies while avoiding experimental artifacts.

Research Strategies for Nutritional and Physical Activity Epidemiology and Cancer Prevention

Very large international and ethnic differences in cancer rates exist, are minimally explained by genetic factors, and show the huge potential for cancer prevention. A substantial portion of the differences in cancer rates can be explained by modifiable factors, and many important relationships have been documented between diet, physical activity, and obesity, and incidence of important cancers. Other related factors, such as the microbiome and the metabolome, are emerging as important intermediary components in cancer prevention. It is possible with the incorporation of newer technologies and studies including long follow-up and evaluation of effects across the life cycle, additional convincing results will be produced. However, several challenges exist for cancer researchers; for example, measurement of diet and physical activity, and lack of standardization of samples for microbiome collection, and validation of metabolomic studies. The United States National Cancer Institute convened the Research Strategies for Nutritional and Physical Activity Epidemiology and Cancer Prevention Workshop on June 28-29, 2016, in Rockville, Maryland, during which the experts addressed the state of the science and areas of emphasis. This current paper reflects the state of the science and priorities for future research. Cancer Epidemiol Biomarkers Prev; 27(3); 233-44. ©2017 AACR.

Microbiome measurement: Possibilities and pitfalls

Microbiome research is an emerging field in medical sciences. Several studies have made headways in understanding the influence of microbes on our health and disease states. Further progress in mapping microbiome populations across different body sites and understanding the underlying mechanisms of microbiome-host interactions depends critically on study design, collection protocols, analytical genetic techniques, and reference databases. In particular, a shift has appeared going from small sample collections to large-scale population studies (with extensive phenotypic information including disease status) which calls for some adaptions. In this review we will focus on gut microbiome profiling using the 16S ribosomal RNA approach in the setting of large-scale population studies, and discuss some novel developments.

Reproducibility of assessing fecal microbiota in chronic constipation

BACKGROUND

While limited data suggest that the fecal microbiota in healthy people is stable over time, the intraindividual variability of the fecal microbiota in constipated patients is unknown.

METHODS

This study evaluated the intraindividual reproducibility of fecal microbiota analyzed with 16S rRNA gene sequencing in two stool samples collected without and after a laxative, respectively, in 25 healthy people and 25 constipated women. Participants completed a food record for 3 d before the stool collection. Colonic transit was measured with scintigraphy.

KEY RESULTS

The constipated patients were older (48±15 vs 39±10 y, P=.02) than healthy participants but had a similar BMI. The total daily caloric intake was less (P=.005) in constipated (1265±350 kcal) than healthy participants (1597±402 kcal). Fourteen patients but only two controls (P<.005), had delayed colonic transit. For most measures of alpha (eg, Observed OTU number, Shannon index) and beta diversity (eg, Bray-Curtis dissimilarity, UniFrac, phyla level abundance), the ICCs between two stool samples were high, indicating moderate or strong agreement, and similar in healthy people and constipated patients. The ICC for the weighted UniFrac distance, which is weighted by abundance, was lower than its unweighted counterpart, indicating that the unweighted measure is more robust and reproducible.

CONCLUSIONS AND INFERENCES

The intraindividual reproducibility of fecal microbiota in constipated patients is high and comparable to healthy participants. For most purposes, evaluating the fecal microbiota in a single stool sample should generally suffice in adequately powered studies of healthy and constipated patients.

Collection of non-meconium stool on fecal occult blood cards is an effective method for fecal microbiota studies in infants

BACKGROUND

Effective methods are needed to collect fecal samples from children for large-scale microbiota studies. Stool collected on fecal occult blood test (FOBT) cards that can be mailed provides an effective solution; however, the quality of sequencing resulting from this method is unknown. The aim of this study is to compare microbiota metrics of 16S ribosomal RNA (rRNA) gene sequencing from stool and meconium collected on FOBT cards with stool collected in an Eppendorf tube (ET) under different conditions.

METHODS

Eight stool samples from children in diapers aged 0 month-2 years and three meconium samples were collected and stored as follows: (1) ≤ 2 days at room temperature (RT) in an ET, (2) 7 days at - 80 °C in an ET, (3) 3-5 days at RT on a FOBT card, (4) 7 days at RT on a FOBT card, and (5) 7 days at - 80 °C on a FOBT card. Samples stored at - 80 °C were frozen immediately. Each specimen/condition underwent 16S rRNA gene sequencing with replicates on the Illumina MiSeq. Alpha and beta diversity measures and relative abundance of major phyla were compared between storage conditions and container (ET vs. FOBT card), with pairwise comparison between different storage conditions and the "standard" of 7 days at - 80 °C in an ET and fresh stool in an ET.

RESULTS

Stool samples clustered mainly by individual diaper (P < 10^-5, Adonis), rather than by storage condition (P = 0.42) or container (P = 0.16). However, meconium samples clustered more by container (P = 0.002) than by individual diaper (P = 0.009) and storage condition (P = 0.02). Additionally, there were no differences in alpha diversity measures and relative abundance of major phyla after Bonferroni correction between stool stored on a FOBT card at RT for 7 days with stool stored in an ET tube at - 80 °C; differences in alpha diversity were seen however when compared to fresh stool in an ET. Overall, based on the intraclass correlation coefficient (ICC), the different storage containers/conditions are reliable in preserving the microbial memberships and slightly less reliable in preserving the alpha diversity and relative microbial composition of infant stool.

CONCLUSIONS

Acknowledging certain limitations, FOBT cards may be a useful tool in large-scale stool microbiota studies in children requiring outpatient follow-up where only small amounts of stool can be obtained, but should not be used when studying meconium.

Evaluation of Copan FecalSwab as Specimen Type for Use in Xpert C. difficile Assay

Liquid-based microbiology (LBM) devices incorporating flocked swabs and preservation medium ease transport of specimens and improve specimen yield compared to traditional fiber wound swabs; however, the performance of LBM collection devices has not been evaluated in many molecular assays. It is unclear how the differences in matrix and specimen loading with an LBM device will affect test performance compared to traditional collection devices. The purpose of this study was to evaluate the performance of specimens collected in FecalSwab transport medium (Copan Diagnostics, Murrieta, CA) compared to unpreserved stool using the Cepheid Xpert C. difficile assay (Cepheid, Sunnyvale, CA). Results equivalent to unpreserved stool samples were obtained when 400 μl of FecalSwab-preserved stool was employed in the Xpert assay. The positive and negative percent agreement of specimens inoculated with FecalSwab medium (n = 281) was 97.0% (95% confidence interval [CI], 90.9 to 96.4%) and 99.4% (95% CI, 96.4 to 99.9%), respectively, compared to reference results obtained using unpreserved stool. Throughout this study, only four discrepant results occurred when comparing preserved specimens to unpreserved stool specimens in the Xpert C. difficile PCR assay. Post discrepant analysis, using the BD MAX Cdiff assay, the specificity and sensitivity both increased to 100%. The high positive and negative percent agreements observed in this study suggest that stool preserved in FecalSwab media yields equivalent results to using unpreserved stool when tested on the Xpert C. difficile assay, allowing laboratories to adopt this liquid-based microbiology collection device.

Comparison of Fecal Collection Methods for Microbiota Studies in Bangladesh

To our knowledge, fecal microbiota collection methods have not been evaluated in low- and middle-income countries. Therefore, we evaluated five different fecal sample collection methods for technical reproducibility, stability, and accuracy within the Health Effects of Arsenic Longitudinal Study (HEALS) in Bangladesh. Fifty participants from the HEALS provided fecal samples in the clinic which were aliquoted into no solution, 95% ethanol, RNAlater, postdevelopment fecal occult blood test (FOBT) cards, and fecal immunochemical test (FIT) tubes. Half of the aliquots were frozen immediately at -80°C (day 0) and the remaining samples were left at ambient temperature for 96 h and then frozen (day 4). Intraclass correlation coefficients (ICC) were calculated for the relative abundances of the top three phyla, for two alpha diversity measures, and for four beta diversity measures. The duplicate samples had relatively high ICCs for technical reproducibility at day 0 and day 4 (range, 0.79 to 0.99). The FOBT card and samples preserved in RNAlater and 95% ethanol had the highest ICCs for stability over 4 days. The FIT tube had lower stability measures overall. In comparison to the "gold standard" method using immediately frozen fecal samples with no solution, the ICCs for many of the microbial metrics were low, but the rank order appeared to be preserved as seen by the Spearman correlation. The FOBT cards, 95% ethanol, and RNAlater were effective fecal preservatives. These fecal collection methods are optimal for future cohort studies, particularly in low- and middle-income countries.IMPORTANCE The collection of fecal samples in prospective cohort studies is essential to provide the opportunity to study the effect of the human microbiota on numerous health conditions. However, these collection methods have not been adequately tested in low- and middle-income countries. We present estimates of technical reproducibility, stability at ambient temperature for 4 days, and accuracy comparing a "gold standard" for fecal samples in no solution, 95% ethanol, RNAlater, postdevelopment fecal occult blood test cards, and fecal immunochemical test tubes in a study conducted in Bangladesh. Fecal occult blood test cards and fecal samples stored in 95% ethanol or RNAlater adequately preserve fecal samples in this setting. Therefore, new studies in low- and middle-income countries should include collection of fecal samples using fecal occult blood test cards, 95% ethanol, or RNAlater for prospective cohort studies.

Correcting for Microbial Blooms in Fecal Samples during Room-Temperature Shipping

The use of sterile swabs is a convenient and common way to collect microbiome samples, and many studies have shown that the effects of room-temperature storage are smaller than physiologically relevant differences between subjects. However, several bacterial taxa, notably members of the class Gammaproteobacteria, grow at room temperature, sometimes confusing microbiome results, particularly when stability is assumed. Although comparative benchmarking has shown that several preservation methods, including the use of 95% ethanol, fecal occult blood test (FOBT) and FTA cards, and Omnigene-GUT kits, reduce changes in taxon abundance during room-temperature storage, these techniques all have drawbacks and cannot be applied retrospectively to samples that have already been collected. Here we performed a meta-analysis using several different microbiome sample storage condition studies, showing consistent trends in which specific bacteria grew (i.e., "bloomed") at room temperature, and introduce a procedure for removing the sequences that most distort analyses. In contrast to similarity-based clustering using operational taxonomic units (OTUs), we use a new technique called "Deblur" to identify the exact sequences corresponding to blooming taxa, greatly reducing false positives and also dramatically decreasing runtime. We show that applying this technique to samples collected for the American Gut Project (AGP), for which participants simply mail samples back without the use of ice packs or other preservatives, yields results consistent with published microbiome studies performed with frozen or otherwise preserved samples. IMPORTANCE In many microbiome studies, the necessity to store samples at room temperature (i.e., remote fieldwork) and the ability to ship samples without hazardous materials that require special handling training, such as ethanol (i.e., citizen science efforts), is paramount. However, although room-temperature storage for a few days has been shown not to obscure physiologically relevant microbiome differences between comparison groups, there are still changes in specific bacterial taxa, notably, in members of the class Gammaproteobacteria, that can make microbiome profiles difficult to interpret. Here we identify the most problematic taxa and show that removing sequences from just a few fast-growing taxa is sufficient to correct microbiome profiles.

Comparison of Collection Methods for Fecal Samples in Microbiome Studies

Prospective cohort studies are needed to assess the relationship between the fecal microbiome and human health and disease. To evaluate fecal collection methods, we determined technical reproducibility, stability at ambient temperature, and accuracy of 5 fecal collection methods (no additive, 95% ethanol, RNAlater Stabilization Solution, fecal occult blood test cards, and fecal immunochemical test tubes). Fifty-two healthy volunteers provided fecal samples at the Mayo Clinic in Rochester, Minnesota, in 2014. One set from each sample collection method was frozen immediately, and a second set was incubated at room temperature for 96 hours and then frozen. Intraclass correlation coefficients (ICCs) were calculated for the relative abundance of 3 phyla, 2 alpha diversity metrics, and 4 beta diversity metrics. Technical reproducibility was high, with ICCs for duplicate fecal samples between 0.64 and 1.00. Stability for most methods was generally high, although the ICCs were below 0.60 for 95% ethanol in metrics that were more sensitive to relative abundance. When compared with fecal samples that were frozen immediately, the ICCs were below 0.60 for the metrics that were sensitive to relative abundance; however, the remaining 2 alpha diversity and 3 beta diversity metrics were all relatively accurate, with ICCs above 0.60. In conclusion, all fecal sample collection methods appear relatively reproducible, stable, and accurate. Future studies could use these collection methods for microbiome analyses.

The gut microbiota in conventional and serrated precursors of colorectal cancer

BACKGROUND

Colorectal cancer is a heterogeneous disease arising from at least two precursors-the conventional adenoma (CA) and the serrated polyp. We and others have previously shown a relationship between the human gut microbiota and colorectal cancer; however, its relationship to the different early precursors of colorectal cancer is understudied. We tested, for the first time, the relationship of the gut microbiota to specific colorectal polyp types.

RESULTS

Gut microbiota were assessed in 540 colonoscopy-screened adults by 16S rRNA gene sequencing of stool samples. Participants were categorized as CA cases (n = 144), serrated polyp cases (n = 73), or polyp-free controls (n = 323). CA cases were further classified as proximal (n = 87) or distal (n = 55) and as non-advanced (n = 121) or advanced (n = 22). Serrated polyp cases were further classified as hyperplastic polyp (HP; n = 40) or sessile serrated adenoma (SSA; n = 33). We compared gut microbiota diversity, overall composition, and normalized taxon abundance among these groups. CA cases had lower species richness in stool than controls (p = 0.03); in particular, this association was strongest for advanced CA cases (p = 0.004). In relation to overall microbiota composition, only distal or advanced CA cases differed significantly from controls (p = 0.02 and p = 0.002). In taxon-based analysis, stool of CA cases was depleted in a network of Clostridia operational taxonomic units from families Ruminococcaceae, Clostridiaceae, and Lachnospiraceae, and enriched in the classes Bacilli and Gammaproteobacteria, order Enterobacteriales, and genera Actinomyces and Streptococcus (all q < 0.10). SSA and HP cases did not differ in diversity or composition from controls, though sample size for these groups was small. Few taxa were differentially abundant between HP cases or SSA cases and controls; among them, class Erysipelotrichi was depleted in SSA cases.

CONCLUSIONS

Our results indicate that gut microbes may play a role in the early stages of colorectal carcinogenesis through the development of CAs. Findings may have implications for developing colorectal cancer prevention therapies targeting early microbial drivers of colorectal carcinogenesis.

Examining the potential use and long-term stability of guaiac faecal occult blood test cards for microbial DNA 16S rRNA sequencing

Aims

With a growing interest in the influence the gut microbiome has on the development of colorectal cancer (CRC), we investigated the feasibility and stability of isolating and typing microbial DNA from guaiac faecal occult blood test (gFOBt) cards. This has the future potential to screen the microbial populations present in confirmed colorectal neoplasia cases with aims to predict the presence and development of CRC.

Methods

Fresh stool samples from three healthy volunteers were applied to gFOBt cards. DNA was extracted from both the cards and fresh stool samples. A series of additional cards were prepared from one volunteer, and extracted at time points between 2 weeks and 3 years. The V4 region of the 16S rRNA gene was amplified and sequenced on an Illumina MiSeq at 2×250 bp read lengths. Data were analysed using QIIME software.

Results

Samples were grouped both by volunteer and by type (fresh or gFOBt), and compared a variety of ways: visual inspection of taxa, α and β diversity, intraclass correlation. In all comparisons, samples grouped by volunteer, and not by sample type. The different time points showed no appreciable differences with increased storage time.

Conclusions

This study has demonstrated that there is good concordance between microbial DNA isolated from fresh stool sample, and from the matched gFOBt card. Samples stored for up to 3 years showed no detrimental effect on measureable microbial DNA. This study has important future implications for investigating microbial influence on CRC development and other pathologies.

DNA from fecal immunochemical test can replace stool for detection of colonic lesions using a microbiota-based model

BACKGROUND

There is a significant demand for colorectal cancer (CRC) screening methods that are noninvasive, inexpensive, and capable of accurately detecting early stage tumors. It has been shown that models based on the gut microbiota can complement the fecal occult blood test and fecal immunochemical test (FIT). However, a barrier to microbiota-based screening is the need to collect and store a patient's stool sample.

RESULTS

Using stool samples collected from 404 patients, we tested whether the residual buffer containing resuspended feces in FIT cartridges could be used in place of intact stool samples. We found that the bacterial DNA isolated from FIT cartridges largely recapitulated the community structure and membership of patients' stool microbiota and that the abundance of bacteria associated with CRC were conserved. We also found that models for detecting CRC that were generated using bacterial abundances from FIT cartridges were equally predictive as models generated using bacterial abundances from stool.

CONCLUSIONS

These findings demonstrate the potential for using residual buffer from FIT cartridges in place of stool for microbiota-based screening for CRC. This may reduce the need to collect and process separate stool samples and may facilitate combining FIT and microbiota-based biomarkers into a single test. Additionally, FIT cartridges could constitute a novel data source for studying the role of the microbiome in cancer and other diseases.

Comparison of Collection Methods for Fecal Samples for Discovery Metabolomics in Epidemiologic Studies

BACKGROUND

The gut metabolome may be associated with the incidence and progression of numerous diseases. The composition of the gut metabolome can be captured by measuring metabolite levels in the feces. However, there are little data describing the effect of fecal sample collection methods on metabolomic measures.

METHODS

We collected fecal samples from 18 volunteers using four methods: no solution, 95% ethanol, fecal occult blood test (FOBT) cards, and fecal immunochemical test (FIT). One set of samples was frozen after collection (day 0), and for 95% ethanol, FOBT, and FIT, a second set was frozen after 96 hours at room temperature. We evaluated (i) technical reproducibility within sample replicates, (ii) stability after 96 hours at room temperature for 95% ethanol, FOBT, and FIT, and (iii) concordance of metabolite measures with the putative "gold standard," day 0 samples without solution.

RESULTS

Intraclass correlation coefficients (ICC) estimating technical reproducibility were high for replicate samples for each collection method. ICCs estimating stability at room temperature were high for 95% ethanol and FOBT (median ICC > 0.87) but not FIT (median ICC = 0.52). Similarly, Spearman correlation coefficients (rs) estimating metabolite concordance with the "gold standard" were higher for 95% ethanol (median rs = 0.82) and FOBT (median rs = 0.70) than for FIT (median rs = 0.40).

CONCLUSIONS

Metabolomic measurements appear reproducible and stable in fecal samples collected with 95% ethanol or FOBT. Concordance with the "gold standard" is highest with 95% ethanol and acceptable with FOBT.

IMPACT

Future epidemiologic studies should collect feces using 95% ethanol or FOBT if interested in studying fecal metabolomics. Cancer Epidemiol Biomarkers Prev; 25(11); 1483-90. ©2016 AACR.

An introduction to microbiome analysis for human biology applications

Research examining the gut microbiota is currently exploding, and results are providing new perspectives on human biology. Factors such as host diet and physiology influence the composition and function of the gut microbiota, which in turn affects human nutrition, health, and behavior via interactions with metabolism, the immune system, and the brain. These findings represent an exciting new twist on familiar topics, and as a result, gut microbiome research is likely to provide insight into unresolved biological mechanisms driving human health. However, much remains to be learned about the broader ecological and evolutionary contexts within which gut microbes and humans are affecting each other. Here, I outline the procedures for generating data describing the gut microbiota with the goal of facilitating the wider integration of microbiome analyses into studies of human biology. I describe the steps involved in sample collection, DNA extraction, PCR amplification, high-throughput sequencing, and bioinformatics. While this review serves only as an introduction to these topics, it provides sufficient resources for researchers interested in launching new microbiome initiatives. As knowledge of these methods spreads, microbiome analysis should become a standard tool in the arsenal of human biology research.

Tiny microbes, enormous impacts: what matters in gut microbiome studies?

Many factors affect the microbiomes of humans, mice, and other mammals, but substantial challenges remain in determining which of these factors are of practical importance. Considering the relative effect sizes of both biological and technical covariates can help improve study design and the quality of biological conclusions. Care must be taken to avoid technical bias that can lead to incorrect biological conclusions. The presentation of quantitative effect sizes in addition to P values will improve our ability to perform meta-analysis and to evaluate potentially relevant biological effects. A better consideration of effect size and statistical power will lead to more robust biological conclusions in microbiome studies.

Shifts in the Fecal Microbiota Associated with Adenomatous Polyps

BACKGROUND

Adenomatous polyps are the most common precursor to colorectal cancer, the second leading cause of cancer-related death in the United States. We sought to learn more about early events of carcinogenesis by investigating shifts in the gut microbiota of patients with adenomas.

METHODS

We analyzed 16S rRNA gene sequences from the fecal microbiota of patients with adenomas (n = 233) and without (n = 547).

RESULTS

Multiple taxa were significantly more abundant in patients with adenomas, including Bilophila, Desulfovibrio, proinflammatory bacteria in the genus Mogibacterium, and multiple Bacteroidetes species. Patients without adenomas had greater abundances of Veillonella, Firmicutes (Order Clostridia), and Actinobacteria (family Bifidobacteriales). Our findings were consistent with previously reported shifts in the gut microbiota of colorectal cancer patients. Importantly, the altered adenoma profile is predicted to increase primary and secondary bile acid production, as well as starch, sucrose, lipid, and phenylpropanoid metabolism.

CONCLUSIONS

These data hint that increased sugar, protein, and lipid metabolism along with increased bile acid production could promote a colonic environment that supports the growth of bile-tolerant microbes such as Bilophilia and Desulfovibrio In turn, these microbes may produce genotoxic or inflammatory metabolites such as H₂S and secondary bile acids, which could play a role in catalyzing adenoma development and eventually colorectal cancer.

IMPACT

This study suggests a plausible biological mechanism to explain the links between shifts in the microbiota and colorectal cancer. This represents a first step toward resolving the complex interactions that shape the adenoma-carcinoma sequence of colorectal cancer and may facilitate personalized therapeutics focused on the microbiota. Cancer Epidemiol Biomarkers Prev; 26(1); 85-94. ©2016 AACR.

Metabolic modeling with Big Data and the gut microbiome

The recent advances in high-throughput omics technologies have enabled researchers to explore the intricacies of the human microbiome. On the clinical front, the gut microbial community has been the focus of many biomarker-discovery studies. While the recent deluge of high-throughput data in microbiome research has been vastly informative and groundbreaking, we have yet to capture the full potential of omics-based approaches. Realizing the promise of multi-omics data will require integration of disparate omics data, as well as a biologically relevant, mechanistic framework - or metabolic model - on which to overlay these data. Also, a new paradigm for metabolic model evaluation is necessary. Herein, we outline the need for multi-omics data integration, as well as the accompanying challenges. Furthermore, we present a framework for characterizing the ecology of the gut microbiome based on metabolic network modeling.

Common methods for fecal sample storage in field studies yield consistent signatures of individual identity in microbiome sequencing data

Field studies of wild vertebrates are frequently associated with extensive collections of banked fecal samples—unique resources for understanding ecological, behavioral, and phylogenetic effects on the gut microbiome. However, we do not understand whether sample storage methods confound the ability to investigate interindividual variation in gut microbiome profiles. Here, we extend previous work on storage methods for gut microbiome samples by comparing immediate freezing, the gold standard of preservation, to three methods commonly used in vertebrate field studies: lyophilization, storage in ethanol, and storage in RNAlater. We found that the signature of individual identity consistently outweighed storage effects: alpha diversity and beta diversity measures were significantly correlated across methods, and while samples often clustered by donor, they never clustered by storage method. Provided that all analyzed samples are stored the same way, banked fecal samples therefore appear highly suitable for investigating variation in gut microbiota. Our results open the door to a much-expanded perspective on variation in the gut microbiome across species and ecological contexts.

Microbiome-wide association studies link dynamic microbial consortia to disease

Rapid advances in DNA sequencing, metabolomics, proteomics and computational tools are dramatically increasing access to the microbiome and identification of its links with disease. In particular, time-series studies and multiple molecular perspectives are facilitating microbiome-wide association studies, which are analogous to genome-wide association studies. Early findings point to actionable outcomes of microbiome-wide association studies, although their clinical application has yet to be approved. An appreciation of the complexity of interactions among the microbiome and the host's diet, chemistry and health, as well as determining the frequency of observations that are needed to capture and integrate this dynamic interface, is paramount for developing precision diagnostics and therapies that are based on the microbiome.

Preservation Methods Differ in Fecal Microbiome Stability, Affecting Suitability for Field Studies

Our study, spanning 15 individuals and over 1,200 samples, provides our most comprehensive view to date of storage and stabilization effects on stool. We tested five methods for preserving human and dog fecal specimens for periods of up to 8 weeks, including the types of variation often encountered under field conditions, such as freeze-thaw cycles and high temperature fluctuations. We show that several cost-effective methods provide excellent microbiome stability out to 8 weeks, opening up a range of field studies with humans and wildlife that would otherwise be cost-prohibitive.

Immediate freezing at −20°C or below has been considered the gold standard for microbiome preservation, yet this approach is not feasible for many field studies, ranging from anthropology to wildlife conservation. Here we tested five methods for preserving human and dog fecal specimens for periods of up to 8 weeks, including such types of variation as freeze-thaw cycles and the high temperature fluctuations often encountered under field conditions. We found that three of the methods—95% ethanol, FTA cards, and the OMNIgene Gut kit—can preserve samples sufficiently well at ambient temperatures such that differences at 8 weeks are comparable to differences among technical replicates. However, even the worst methods, including those with no fixative, were able to reveal microbiome differences between species at 8 weeks and between individuals after a week, allowing meta-analyses of samples collected using various methods when the effect of interest is expected to be larger than interindividual variation (although use of a single method within a study is strongly recommended to reduce batch effects). Encouragingly for FTA cards, the differences caused by this method are systematic and can be detrended. As in other studies, we strongly caution against the use of 70% ethanol. The results, spanning 15 individuals and over 1,200 samples, provide our most comprehensive view to date of storage effects on stool and provide a paradigm for the future studies of other sample types that will be required to provide a global view of microbial diversity and its interaction among humans, animals, and the environment.

IMPORTANCE Our study, spanning 15 individuals and over 1,200 samples, provides our most comprehensive view to date of storage and stabilization effects on stool. We tested five methods for preserving human and dog fecal specimens for periods of up to 8 weeks, including the types of variation often encountered under field conditions, such as freeze-thaw cycles and high temperature fluctuations. We show that several cost-effective methods provide excellent microbiome stability out to 8 weeks, opening up a range of field studies with humans and wildlife that would otherwise be cost-prohibitive.

Characterization of the gut microbiome in epidemiologic studies: the multiethnic cohort experience

PURPOSE

The development of next-generation sequencing and accompanying bioinformatics tools has revolutionized characterization of microbial communities. As interest grows in the role of the human microbiome in health and disease, so does the need for well-powered, robustly designed epidemiologic studies. Here, we discuss sources of bias that can arise in gut microbiome research.

METHODS

Research comparing methods of specimen collection, preservation, processing, and analysis of gut microbiome samples is reviewed. Although selected studies are primarily based on the gut, many of the same principles are applicable to samples derived from other anatomical sites. Methods for participant recruitment and sampling of the gut microbiome implemented in an ongoing population-based study, the Multiethnic Cohort (MEC), are also described.

RESULTS

Variation in methodologies can influence the results of human microbiome studies. To help minimize bias, techniques such as sample homogenization, addition of internal standards, and quality filtering should be adopted in protocols. Within the MEC, participant response rates to stool sample collection were comparable to other studies, and in-home stool sample collection yields sufficient high-quality DNA for gut microbiome analysis.

CONCLUSIONS

Application of standardized and quality controlled methods in human microbiome studies is necessary to ensure data quality and comparability among studies.