Collecting Fecal Samples for Microbiome Analyses in Epidemiology Studies

Household paired design reduces variance and increases power in multi-city gut microbiome study in multiple sclerosis

BACKGROUND

Evidence for a role of human gut microbiota in multiple sclerosis (MS) risk is mounting, yet large variability is seen across studies. This is, in part, due to the lack of standardization of study protocols, sample collection methods, and sequencing approaches.

OBJECTIVE

This study aims to address the effect of a household experimental design, sample collection, and sequencing approaches in a gut microbiome study in MS subjects from a multi-city study population.

METHODS

We analyzed 128 MS patient and cohabiting healthy control pairs from the International MS Microbiome Study (iMSMS). A total of 1005 snap-frozen or desiccated Q-tip stool samples were collected and evaluated using 16S and shallow whole-metagenome shotgun sequencing.

RESULTS

The intra-individual variance observed by different collection strategies was dramatically lower than inter-individual variance. Shallow shotgun highly correlated with 16S sequencing. Participant house and recruitment site accounted for the two largest sources of microbial variance, while higher microbial similarity was seen in household-matched participants as hypothesized. A significant proportion of the variance in dietary intake was also dominated by geographic distance.

CONCLUSION

A household pair study largely overcomes common inherent limitations and increases statistical power in population-based microbiome studies.

Performance comparison of fecal preservative and stock solutions for gut microbiome storage at room temperature

The gut microbiome, which is symbiotic within the human body, assists in human digestion. It plays significant roles in identifying intestinal disease as well as in maintaining a healthy body with functional immune and metabolic activities. To confirm the consistency of fecal intestinal microbial research, it is necessary to study the changes in intestinal microbial flora according to the fecal collection solution and storage period. We collected fecal samples from three healthy Korean adults. To examine the efficacy of fecal collection solution, we used NBgene-Gut, OMNIgene-Gut, 70% ethanol (Ethanol-70%), and RNAlater. The samples were stored for up to two months at room temperature using three different methods, and we observed changes in microbial communities over time. We analyzed clusters of changes in the microbial flora by observing fecal stock solutions and metagenome sequencing performed over time. In particular, we confirmed the profiling of alpha and beta diversity and microbial classification according to the differences in intestinal environment among individuals. We also confirmed that the microbial profile remained stable for two months and that the microbial profile did not change significantly over time. In addition, our results suggest the possibility of verifying microbial profiling even for long-term storage of a single sample. In conclusion, collecting fecal samples using a stock solution rather than freezing feces seems to be relatively reproducible and stable for GUT metagenome analysis. Therefore, stock solution tubes in intestinal microbial research can be used without problems.

A Guide to Diet-Microbiome Study Design

Intense recent interest in understanding how the human gut microbiome influences health has kindled a concomitant interest in linking dietary choices to microbiome variation. Diet is known to be a driver of microbiome variation, and yet the precise mechanisms by which certain dietary components modulate the microbiome, and by which the microbiome produces byproducts and secondary metabolites from dietary components, are not well-understood. Interestingly, despite the influence of diet on the gut microbiome, the majority of microbiome studies published to date contain little or no analysis of dietary intake. Although an increasing number of microbiome studies are now collecting some form of dietary data or even performing diet interventions, there are no clear standards in the microbiome field for how to collect diet data or how to design a diet-microbiome study. In this article, we review the current practices in diet-microbiome analysis and study design and make several recommendations for best practices to provoke broader discussion in the field. We recommend that microbiome studies include multiple consecutive microbiome samples per study timepoint or phase and multiple days of dietary history prior to each microbiome sample whenever feasible. We find evidence that direct effects of diet on the microbiome are likely to be observable within days, while the length of an intervention required for observing microbiome-mediated effects on the host phenotype or host biomarkers, depending on the outcome, may be much longer, on the order of weeks or months. Finally, recent studies demonstrating that diet-microbiome interactions are personalized suggest that diet-microbiome studies should either include longitudinal sampling within individuals to identify personalized responses, or should include an adequate number of participants spanning a range of microbiome types to identify generalized responses.

The promise and challenge of cancer microbiome research

Many microbial agents have been implicated as contributors to cancer genesis and development, and the search to identify and characterize new cancer-related organisms is ongoing. Modern developments in methodologies, especially culture-independent approaches, have accelerated and driven this research. Recent work has shed light on the multifaceted role that the community of organisms in and on the human body plays in cancer onset, development, detection, treatment, and outcome. Much remains to be discovered, however, as methodological variation and functional testing of statistical correlations need to be addressed for the field to advance.

Variations of Gut Microbiome Profile Under Different Storage Conditions and Preservation Periods: A Multi-Dimensional Evaluation

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.

Adolescent follow-up in the Health Outcomes and Measures of the Environment (HOME) Study: cohort profile

PURPOSE

Environmental chemical exposures may adversely affect an array of adolescent health outcomes. Thus, we used the Health Outcomes and Measures of the Environment (HOME) study, a prospective cohort that recruited pregnant women and conducted longitudinal follow-up on children over the first 12 years of life, to determine if and when chemical exposures affect adolescent health.

PARTICIPANTS

We recruited 468 pregnant women (age range: 18-45 years) from the Cincinnati, Ohio region to participate in a cohort study between March 2003 and January 2006. Follow-up included two clinic and one home visits during pregnancy, a delivery hospital visit, and four home and six clinic visits when children were aged 4 weeks and 1, 2, 3, 4, 5 and 8 years. Of 441 children available for follow-up, 396 (90%) completed at least one follow-up and 256 (58%) completed the most recent follow-up at 12 years of age (range: 11-14).

FINDINGS TO DATE

Our new measures include maternal/child report of internalising symptoms, neuroimaging, dual-energy X-ray absorptiometry-derived estimates of lean/adipose tissue and bone mineral density, and cardiometabolic risk biomarkers. We assessed adolescent exposure to perfluoroalkyl substances, phenols, phthalates and flame retardants. Participants completing follow-up at 12 years of age were similar to the original cohort in terms of baseline factors. Most children had typical and expected values for this age on measures of internalising symptoms, body composition, bone density and cardiometabolic risk markers. Notably, 36% and 11% of children had scores indicative of potential anxiety and depressive disorders, respectively. Approximately 35% of children were overweight or obese, with higher prevalence among girls. Thirty-three per cent of children had borderline or high triglyceride concentrations (>90 mg/dL).

FUTURE PLANS

We will examine associations of early life environmental chemical exposures with adolescent health measures while considering potential periods of heightened susceptibility and mixture effects.

TRIAL REGISTRATION NUMBER

NCT00129324.

Comparative Study of Salivary, Duodenal, and Fecal Microbiota Composition Across Adult Celiac Disease

Background: Growing evidence suggests that an altered microbiota composition contributes to the pathogenesis and clinical features in celiac disease (CD). We performed a comparative analysis of the gut microbiota in adulthood CD to evaluate whether: (i) dysbiosis anticipates mucosal lesions, (ii) gluten-free diet restores eubiosis, (iii) refractory CD has a peculiar microbial signature, and (iv) salivary and fecal communities overlap the mucosal one. Methods: This is a cross-sectional study where a total of 52 CD patients, including 13 active CD, 29 treated CD, 4 refractory CD, and 6 potential CD, were enrolled in a tertiary center together with 31 controls. A 16S rRNA-based amplicon metagenomics approach was applied to determine the microbiota structure and composition of salivary, duodenal mucosa, and stool samples, followed by appropriate bioinformatic analyses. Results: A reduction of both α- and β-diversity in CD, already evident in the potential form and achieving nadir in refractory CD, was evident. Taxonomically, mucosa displayed a significant abundance of Proteobacteria and an expansion of Neisseria, especially in active patients, while treated celiacs showed an intermediate profile between active disease and controls. The saliva community mirrored the mucosal one better than stool. Conclusion: Expansion of pathobiontic species anticipates villous atrophy and achieves the maximal divergence from controls in refractory CD. Gluten-free diet results in incomplete recovery. The overlapping results between mucosal and salivary samples indicate the use of saliva as a diagnostic fluid.

Dietary Fiber, Gut Microbiota, and Metabolic Regulation-Current Status in Human Randomized Trials

New knowledge about the gut microbiota and its interaction with the host's metabolic regulation has emerged during the last few decades. Several factors may affect the composition of the gut microbiota, including dietary fiber. Dietary fiber is not hydrolyzed by human digestive enzymes, but it is acted upon by gut microbes, and metabolites like short-chain fatty acids are produced. The short-chain fatty acids may be absorbed into the circulation and affect metabolic regulation in the host or be a substrate for other microbes. Some studies have shown improved insulin sensitivity, weight regulation, and reduced inflammation with increases in gut-derived short-chain fatty acids, all of which may reduce the risk of developing metabolic diseases. To what extent a dietary intervention with fiber may affect the human gut microbiota and hence metabolic regulation, is however, currently not well described. The aim of the present review is to summarize recent research on human randomized, controlled intervention studies investigating the effect of dietary fiber on gut microbiota and metabolic regulation. Metabolic regulation is discussed with respect to markers relating to glycemic regulation and lipid metabolism. Taken together, the papers on which the current review is based, suggest that dietary fiber has the potential to change the gut microbiota and alter metabolic regulation. However, due to the heterogeneity of the studies, a firm conclusion describing the causal relationship between gut microbiota and metabolic regulation remains elusive.

Early sexual dimorphism in the developing gut microbiome of northern elephant seals

The gut microbiome is an integral part of a species' ecology, but we know little about how host characteristics impact its development in wild populations. Here, we explored the role of such intrinsic factors in shaping the gut microbiome of northern elephant seals (Mirounga angustirostris) during a critical developmental window of 6 weeks after weaning, when the pups stay ashore without feeding. We found substantial sex differences in the early-life gut microbiome, even though males and females could not yet be distinguished morphologically. Sex and age both explained around 15% of the variation in gut microbial beta diversity, while microbial communities sampled from the same individual showed high levels of similarity across time, explaining another 40% of the variation. Only a small proportion of the variation in beta diversity was explained by health status, assessed by full blood counts, but clinically healthy individuals had a greater microbial alpha diversity than their clinically abnormal peers. Across the post-weaning period, the northern elephant seal gut microbiome was highly dynamic. We found evidence for several colonization and extinction events as well as a decline in Bacteroides and an increase in Prevotella, a pattern that has previously been associated with the transition from nursing to solid food. Lastly, we show that genetic relatedness was correlated with gut microbiome similarity in males but not females, again reflecting early sex differences. Our study represents a naturally diet-controlled and longitudinal investigation of how intrinsic factors shape the early gut microbiome in a species with extreme sex differences in morphology and life history.

Comparison of Methods To Collect Fecal Samples for Microbiome Studies Using Whole-Genome Shotgun Metagenomic Sequencing

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.

Diversity, compositional and functional differences between gut microbiota of children and adults

The gut microbiota has been shown to play diverse roles in human health and disease although the underlying mechanisms have not yet been fully elucidated. Large cohort studies can provide further understanding into inter-individual differences, with more precise characterization of the pathways by which the gut microbiota influences human physiology and disease processes. Here, we aimed to profile the stool microbiome of children and adults from two population-based cohort studies, comprising 2,111 children in the age-range of 9 to 12 years (the Generation R Study) and 1,427 adult individuals in the range of 46 to 88 years of age (the Rotterdam Study). For the two cohorts, 16S rRNA gene profile datasets derived from the Dutch population were generated. The comparison of the two cohorts showed that children had significantly lower gut microbiome diversity. Furthermore, we observed higher relative abundances of genus Bacteroides in children and higher relative abundances of genus Blautia in adults. Predicted functional metagenome analysis showed an overrepresentation of the glycan degradation pathways, riboflavin (vitamin B2), pyridoxine (vitamin B6) and folate (vitamin B9) biosynthesis pathways in children. In contrast, the gut microbiome of adults showed higher abundances of carbohydrate metabolism pathways, beta-lactam resistance, thiamine (vitamin B1) and pantothenic (vitamin B5) biosynthesis pathways. A predominance of catabolic pathways in children (valine, leucine and isoleucine degradation) as compared to biosynthetic pathways in adults (valine, leucine and isoleucine biosynthesis) suggests a functional microbiome switch to the latter in adult individuals. Overall, we identified compositional and functional differences in gut microbiome between children and adults in a population-based setting. These microbiome profiles can serve as reference for future studies on specific human disease susceptibility in childhood, adulthood and specific diseased populations.

Systematic Analysis of Impact of Sampling Regions and Storage Methods on Fecal Gut Microbiome and Metabolome Profiles

The gastrointestinal microbiome and metabolome can provide a new angle to understand the development of health and disease. Stool samples are most frequently used for large-scale cohort studies. Standardized procedures for stool sample handling and storage can be a determining factor for performing microbiome or metabolome studies. In this study, we focused on the effects of stool sampling regions and stool sample storage conditions on variations in the gut microbiome composition and metabolome profile.

The contribution of human gastrointestinal (GI) microbiota and metabolites to host health has recently become much clearer. However, many confounding factors can influence the accuracy of gut microbiome and metabolome studies, resulting in inconsistencies in published results. In this study, we systematically investigated the effects of fecal sampling regions and storage and retrieval conditions on gut microbiome and metabolite profiles from three healthy children. Our analysis indicated that compared to homogenized and snap-frozen samples (standard control [SC]), different sampling regions did not affect microbial community alpha diversity, while a total of 22 of 176 identified metabolites varied significantly across different sampling regions. In contrast, storage conditions significantly influenced the microbiome and metabolome. Short-term room temperature storage had a minimal effect on the microbiome and metabolome profiles. Sample storage in RNALater showed a significant level of variation in both microbiome and metabolome profiles, independent of the storage or retrieval conditions. The effect of RNALater on the metabolome was stronger than the effect on the microbiome, and individual variability between study participants outweighed the effect of RNALater on the microbiome. We conclude that homogenizing stool samples was critical for metabolomic analysis but not necessary for microbiome analysis. Short-term room temperature storage had a minimal effect on the microbiome and metabolome profiles and is recommended for short-term fecal sample storage. In addition, our study indicates that the use of RNALater as a storage medium of stool samples for microbial and metabolomic analyses is not recommended.

IMPORTANCE The gastrointestinal microbiome and metabolome can provide a new angle to understand the development of health and disease. Stool samples are most frequently used for large-scale cohort studies. Standardized procedures for stool sample handling and storage can be a determining factor for performing microbiome or metabolome studies. In this study, we focused on the effects of stool sampling regions and stool sample storage conditions on variations in the gut microbiome composition and metabolome profile.

Impact of Sample Preservation and Manipulation on Insect Gut Microbiome Profiling. A Test Case With Fruit Flies (Diptera, Tephritidae)

High-throughput sequencing (HTS) techniques are of great value for the investigation of microbial communities, and have been extensively used to study the gut microbiome. While most studies focus on the human gut, many others have investigated insects. However, because of the rapid spread of HTS techniques, a lot of variation exists in the protocols for sample preparation. In the present study, we investigated the impact of two widely adopted sample-processing procedures preceding library preparation, i.e., preservation of insect tissue in 70% ethanol (EtOH) and sample dissection. We used the fruit fly Ceratitis capitata (Diptera: Tephritidae) as a model organism and set up two experiments, one comparing the effects of sample manipulation and preservation across life stages and the other across fruit samples from different sources. The results of this study showed no major effects of dissection on the outcome of HTS. However, EtOH preservation did have effects on the recovered gut microbiome, the main effect being a significant reduction of the dominant genus, Providencia, in EtOH-preserved samples. Less abundant bacterial groups were also affected resulting in altered microbial profiles obtained from samples preserved in 70% EtOH. These results have important implications for the planning of future studies and when comparing studies that used different sample preparation protocols.

Minor compositional alterations in faecal microbiota after five weeks and five months storage at room temperature on filter papers

The gut microbiota is recognized as having major impact in health and disease. Sample storage is an important aspect to obtain reliable results. Mostly recommended is immediate freezing, however, this is not always feasible. Faecal occult blood test (FOBT) papers are an appealing solution in such situations, and most studies find these to be applicable, showing no major changes within 7 days storage at room temperature (RT). As fieldwork often requires RT storage for longer periods, evaluation of this is warranted. We performed 16S rRNA gene sequencing of 19 paired faecal samples immediately frozen or kept five weeks and five months at RT on FOBT papers. Alpha-diversity evaluation revealed no effect of FOBT storage, and evaluation of beta-diversity showed that host explained 65% of community variation, while storage method explained 5%. Evaluation of community dispersion and the Firmicutes/Bacteroidetes ratio revealed a larger effect of storage time for fresh-frozen samples. Single taxa evaluation (order-to-genus level) showed significant alterations of four (of 37) genera after five weeks and five genera after five months. When comparing the two timepoints, alterations were only detectable for fresh-frozen samples. Our findings reveal that long term storage on FOBT papers is an applicable approach for microbiota research.

Guidelines for Transparency on Gut Microbiome Studies in Essential and Experimental Hypertension

Hypertension is a complex and modifiable condition in which environmental factors contribute to both onset and progression. Recent evidence has accumulated for roles of diet and the gut microbiome as environmental factors in blood pressure regulation. However, this is complex because gut microbiomes are a unique feature of each individual reflecting that individual’s developmental and environmental history creating caveats for both experimental models and human studies. Here, we describe guidelines for conducting gut microbiome studies in experimental and clinical hypertension. We provide a complete guide for authors on proper design, analyses, and reporting of gut microbiota/microbiome and metabolite studies and checklists that can be used by reviewers and editors to support robust reporting and interpretation. We discuss factors that modulate the gut microbiota in animal (eg, cohort, controls, diet, developmental age, housing, sex, and models used) and human studies (eg, blood pressure measurement and medication, body mass index, demographic characteristics including age, cultural identification, living structure, sex and socioeconomic environment, and exclusion criteria). We also provide best practice advice on sampling, storage of fecal/cecal samples, DNA extraction, sequencing methods (including metagenomics and 16S rRNA), and computational analyses. Finally, we discuss the measurement of short-chain fatty acids, metabolites produced by the gut microbiota, and interpretation of data. These guidelines should support better transparency, reproducibility, and translation of findings in the field of gut microbiota/microbiome in hypertension and cardiovascular disease.

Reproducibility, stability, and accuracy of microbial profiles by fecal sample collection method in three distinct populations

The gut microbiome likely plays a role in the etiology of multiple health conditions, especially those affecting the gastrointestinal tract. Little consensus exists as to the best, standard methods to collect fecal samples for future microbiome analysis. We evaluated three distinct populations (N = 132 participants) using 16S rRNA gene amplicon sequencing data to investigate the reproducibility, stability, and accuracy of microbial profiles in fecal samples collected and stored via fecal occult blood test (FOBT) or Flinders Technology Associates (FTA) cards, fecal immunochemical tests (FIT) tubes, 70% and 95% ethanol, RNAlater, or with no solution. For each collection method, based on relative abundance of select phyla and genera, two alpha diversity metrics, and four beta diversity metrics, we calculated intraclass correlation coefficients (ICCs) to estimate reproducibility and stability, and Spearman correlation coefficients (SCCs) to estimate accuracy of the fecal microbial profile. Comparing duplicate samples, reproducibility ICCs for all collection methods were excellent (ICCs ≥75%). After 4–7 days at ambient temperature, ICCs for microbial profile stability were excellent (≥75%) for most collection methods, except those collected via no-solution and 70% ethanol. SCCs comparing each collection method to immediately-frozen no-solution samples ranged from fair to excellent for most methods; however, accuracy of genus-level relative abundances differed by collection method. Our findings, taken together with previous studies and feasibility considerations, indicated that FOBT/FTA cards, FIT tubes, 95% ethanol, and RNAlater are excellent choices for fecal sample collection methods in future microbiome studies. Furthermore, establishing standard collection methods across studies is highly desirable.

A Customized At-Home Stool Collection Protocol for Use in Microbiome Studies Conducted in Cancer Patient Populations

Fecal specimen collection in the clinical setting is often unfeasible for large population studies, especially because cancer patients on immunotherapy often experience constipation. A method for constructing and using an at-home stool collection kit designed for epidemiological studies in cancer patients is presented. Participation and compliance rates of the collection kit among late-stage cancer patients from an ongoing, longitudinal study are also discussed. The kit includes three different media on which samples are introduced. Using one stool sample, patients collect specimens by smearing stool onto a fecal occult blood test (FOBT) card, containing three slides for collection. Additional specimens from the same stool sample are added to one tube containing 8 mL of RNAlater preservative and one tube containing 8 mL of 95% ethanol. Stool specimens are stored at room temperature and returned to researchers within 3 days of collection. The purpose of this kit is to yield stool specimens on a variety of media that can be preserved for extended periods of time at room temperature and are compatible with multi-omics approaches for specimen analysis. According to leading microbiome researchers and published literature, each collection method is considered optimal for use in large epidemiological studies. Moreover, the kit is comprised of various components that make stool collection easy, so as not to burden the patient and hence maximize overall compliance. Use of this kit in a study of late-stage lung cancer patients had a participation rate of 83% and baseline compliance rate of 58%.

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing

The human gut is colonized by trillions of bacteria that support physiologic functions such as food metabolism, energy harvesting, and regulation of the immune system. Perturbation of the healthy gut microbiome has been suggested to play a role in the development of inflammatory diseases, including multiple sclerosis (MS). Environmental and genetic factors can influence the composition of the microbiome; therefore, identification of microbial communities linked with a disease phenotype has become the first step towards defining the microbiome's role in health and disease. Use of 16S rRNA metagenomic sequencing for profiling bacterial community has helped in advancing microbiome research. Despite its wide use, there is no uniform protocol for 16S rRNA-based taxonomic profiling analysis. Another limitation is the low resolution of taxonomic assignment due to technical difficulties such as smaller sequencing reads, as well as use of only forward (R1) reads in the final analysis due to low quality of reverse (R2) reads. There is need for a simplified method with high resolution to characterize bacterial diversity in a given biospecimen. Advancements in sequencing technology with the ability to sequence longer reads at high resolution have helped to overcome some of these challenges. Present sequencing technology combined with a publicly available metagenomic analysis pipeline such as R-based Divisive Amplicon Denoising Algorithm-2 (DADA2) has helped advance microbial profiling at high resolution, as DADA2 can assign sequence at the genus and species levels. Described here is a guide for performing bacterial profiling using two-step amplification of the V3-V4 region of the 16S rRNA gene, followed by analysis using freely available analysis tools (i.e., DADA2, Phyloseq, and METAGENassist). It is believed that this simple and complete workflow will serve as an excellent tool for researchers interested in performing microbiome profiling studies.

Gut microbial diversity and genus-level differences identified in cervical cancer patients versus healthy controls

OBJECTIVES

The aim of this study was to characterize variation in the gut microbiome of women with locally advanced cervical cancer and compare it to healthy controls.

METHODS

We characterized the 16S rDNA fecal microbiome in 42 cervical cancer patients and 46 healthy female controls. Shannon diversity index (SDI) was used to evaluate alpha (within sample) diversity. Beta (between sample) diversity was examined using principle coordinate analysis (PCoA) of unweighted Unifrac distances. Relative abundance of microbial taxa was compared between samples using Linear Discriminant Analysis Effect Size (LEfSe).

RESULTS

Within cervical cancer patients, bacterial alpha diversity was positively correlated with age (p = 0.22) but exhibited an inverse relationship in control subjects (p < 0.01). Alpha diversity was significantly higher in cervical cancer patients as compared to controls (p < 0.05), though stratification by age suggested this relationship was restricted to older women (>50 years; p < 0.01). Beta diversity (unweighted Unifrac; p < 0.01) also significantly differed between cervical cancer patients and controls. Based on age- and race-adjusted LEfSe analysis, multiple taxa significantly differed between cervical cancer patients and controls. Prevotella, Porphyromonas, and Dialister were significantly enriched in cervical cancer patients, while Bacteroides, Alistipes and members of the Lachnospiracea family were significantly enriched in healthy subjects.

CONCLUSION

Our study suggests differences in gut microbiota diversity and composition between cervical cancer patients and controls. Associations within the gut microbiome by age may reflect etiologic/clinical differences. These findings provide rationale for further study of the gut microbiome in cervical cancer.

Aiginition Longitudinal Biomarker Investigation Of Neurodegeneration (ALBION): study design, cohort description, and preliminary data

Objectives: Aiginition Longitudinal Biomarker Investigation Of Neurodegeneration (ALBION) is a longitudinal ongoing study initiated in 2018 that takes place in the Cognitive Disorders Clinic of Aiginition Hospital of the National and Kapodistrian University of Athens. Its aim is to address several research questions concerning the preclinical and prodromal stage of Alzheimer's disease and explore potential markers for early detection, prediction, and primary prevention of dementia. Methods: We here present the design and the preliminary baseline characteristics of ALBION. The sample of our study consists of people aged over 50 who are concerned about their memory but are cognitively normal (CN) or have mild cognitive deficits. Each participant undergoes an extensive assessment including several demographic, medical, social, environmental, clinical, nutritional, neuropsychological determinants and lifestyle activities. Furthermore, we are collecting data from portable devices, neuroimaging techniques and biological samples (blood, stools, CSF). All participants are assessed annually for a period of 10 years. Results: In total, 47 participants have completed the initial evaluation up to date and are divided in two groups, CN individuals (N = 26) and MCI patients (N = 21), based on their cognitive status. The participants are, on average, 64 years old, 46.3% of the sample is male with an average of 12.73 years of education. MCI patients report more comorbidities and have a lower score in the MMSE test. Regarding APOE status, 2 participants are ε4 homozygotes and 10 ε4 heterozygotes. CSF analyses (Aβ42, Τ-tau, P-tau) revealed no differences between the two groups. Conclusion: The ALBION study offers an opportunity to explore preclinical dementia and identify new and tailored markers, particularly relating to lifestyle. Further investigation of these populations may provide a wider profile of the changes taking place in the preclinical phase of dementia, leading to potentially effective therapeutic and preventive strategies.

Prescribed Drugs and the Microbiome

The interaction between drug use, the microbiome, and the host is complex and multidimensional. Drugs and the microbiota may be risk factors or protective factors for disease. These interactions may explain interpersonal variations in drug efficacy and toxicity, but also interpersonal variations in microbiota composition and functioning, and potential (long-term) side effects from drugs.

Assessment of the impact of different fecal storage protocols on the microbiota diversity and composition: a pilot study

Background

Fecal samples are currently the most commonly studied proxy for gut microbiota. The gold standard of sample handling and storage for microbiota analysis is maintaining the cold chain during sample transfer and immediate storage at − 80 °C. Gut microbiota studies in large-scale, population-based cohorts require a feasible sample collection protocol. We compared the effect of three different storage methods and mock shipment: immediate freezing at − 80 °C, in 95% ethanol stored at room temperature (RT) for 48 h, and on blood collection card stored at RT for 48 h, on the measured composition of fecal microbiota of eight healthy, female volunteers by sequencing the V4 region of the 16S rRNA gene on an Illumina MiSeq.

Results

Shared operational taxonomic units (OTUs) between different methods were 68 and 3% for OTUs > 0.01 and < 0.01% mean relative abundance within each group, respectively. α and β-diversity measures were not significantly impacted by different storage methods. With the exception of Actinobacteria, fecal microbiota profiles at the phylum level were not significantly affected by the storage method. Actinobacteria was significantly higher in samples collected on card compared to immediate freezing (1.6 ± 1.1% vs. 0.4 ± 0.2%, p = 0.005) mainly driven by expansion of Actinobacteria relative abundance in fecal samples stored on card in two individuals. There was no statistically significant difference at lower taxonomic levels tested.

Conclusion

Consistent results of the microbiota composition and structure for different storage methods were observed. Fecal collection on card could be a suitable alternative to immediate freezing for fecal microbiota analysis using 16S rRNA gene amplicon sequencing.

Electronic supplementary material

The online version of this article (10.1186/s12866-019-1519-2) contains supplementary material, which is available to authorized users.

Compositional Analysis of the Human Microbiome in Cancer Research

Gut microbial composition has shown to be associated with obesity, diabetes mellitus, inflammatory bowel disease, colitis, autoimmune disorders, and cancer, among other diseases. Microbiome research has significantly evolved through the years and continues to advance as we develop new and better strategies to more accurately measure its composition and function. Careful selection of study design, inclusion and exclusion criteria of participants, and methodology are paramount to accurately analyze microbial structure. Here we present the most up-to-date available information on methods for gut microbial collection and analysis.

The Microbiome and Irritable Bowel Syndrome - A Review on the Pathophysiology, Current Research and Future Therapy

Irritable bowel syndrome (IBS) is a functional disorder which affects a large proportion of the population globally. The precise etiology of IBS is still unknown, although consensus understanding proposes IBS to be of multifactorial origin with yet undefined subtypes. Genetic and epigenetic factors, stress-related nervous and endocrine systems, immune dysregulation and the brain-gut axis seem to be contributing factors that predispose individuals to IBS. In addition to food hypersensitivity, toxins and adverse life events, chronic infections and dysbiotic gut microbiota have been suggested to trigger IBS symptoms in tandem with the predisposing factors. This review will summarize the pathophysiology of IBS and the role of gut microbiota in relation to IBS. Current methodologies for microbiome studies in IBS such as genome sequencing, metagenomics, culturomics and animal models will be discussed. The myriad of therapy options such as immunoglobulins (immune-based therapy), probiotics and prebiotics, dietary modifications including FODMAP restriction diet and gluten-free diet, as well as fecal transplantation will be reviewed. Finally this review will highlight future directions in IBS therapy research, including identification of new molecular targets, application of 3-D gut model, gut-on-a-chip and personalized therapy.

Body site-dependent variations of microbiota in pancreatic cancer pathophysiology

Lack of specific symptoms and reliable biomarkers, along with aggressive nature and resistance to therapies makes pancreatic cancer (PC) one of the leading causes of death from cancer worldwide. The search for new diagnostic, prognostic, predictive, and therapeutic tools that could improve clinical outcomes of patients has led, in recent years, to the investigation of potential roles for the microbiota in the pathogenesis of this disease. The human microbiota encompasses trillions of microorganisms residing within several body tissues and organs, where they provide beneficial functions for host homeostasis and health. Derangements of the microbial ecology in different anatomic districts have been described in PC, as in many other diseases, both in patients and in animal models. In detail, infection from the gastric pathogen Helicobacter pylori and changes in composition and diversity of oral, intestinal, and pancreatic microbiota have been found to associate with PC. Future research should assess how to potentially exploit such differences in microbiota composition as diagnostic, prognostic, or predictive biomarkers, and as targets for therapeutic interventions, in the hope of improving the dismal prognosis of this insidious cancer.

The Impact of DNA Polymerase and Number of Rounds of Amplification in PCR on 16S rRNA Gene Sequence Data

PCR amplification of 16S rRNA genes is a critical yet underappreciated step in the generation of sequence data to describe the taxonomic composition of microbial communities. Numerous factors in the design of PCR can impact the sequencing error rate, the abundance of chimeric sequences, and the degree to which the fragments in the product represent their abundance in the original sample (i.e., bias). We compared the performance of high fidelity polymerases and various numbers of rounds of amplification when amplifying a mock community and human stool samples. Although it was impossible to derive specific recommendations, we did observe general trends. Namely, using a polymerase with the highest possible fidelity and minimizing the number of rounds of PCR reduced the sequencing error rate, fraction of chimeric sequences, and bias. Evidence of bias at the sequence level was subtle and could not be ascribed to the fragments' fraction of bases that were guanines or cytosines. When analyzing mock community data, the amount that the community deviated from the expected composition increased with the number of rounds of PCR. This bias was inconsistent for human stool samples. Overall, the results underscore the difficulty of comparing sequence data that are generated by different PCR protocols. However, the results indicate that the variation in human stool samples is generally larger than that introduced by the choice of polymerase or number of rounds of PCR.IMPORTANCE A steep decline in sequencing costs drove an explosion in studies characterizing microbial communities from diverse environments. Although a significant amount of effort has gone into understanding the error profiles of DNA sequencers, little has been done to understand the downstream effects of the PCR amplification protocol. We quantified the effects of the choice of polymerase and number of PCR cycles on the quality of downstream data. We found that these choices can have a profound impact on the way that a microbial community is represented in the sequence data. The effects are relatively small compared to the variation in human stool samples; however, care should be taken to use polymerases with the highest possible fidelity and to minimize the number of rounds of PCR. These results also underscore that it is not possible to directly compare sequence data generated under different PCR conditions.

Getting to Know the Gut Microbial Diversity of Metropolitan Buenos Aires Inhabitants

In recent years, the field of immunology has been revolutionized by the growing understanding of the fundamental role of microbiota in the immune system function. The immune system has evolved to maintain a symbiotic relationship with these microbes. The aim of our study was to know in depth the uncharacterized metagenome of the Buenos Aires (BA) city population and its metropolitan area, being the second most populated agglomeration in the southern hemisphere. For this purpose, we evaluated 30 individuals (age: 35.23 ± 8.26 years and BMI: 23.91 ± 3.4 kg/m²), from the general population of BA. The hypervariable regions V3-V4 of the bacterial 16S gene was sequenced by MiSeq-Illumina system, obtaining 47526 ± 4718 sequences/sample. The dominant phyla were Bacteroidetes, Firmicutes, Proteobacteria, Verrucomicrobia, and Actinobacteria. Additionally, we compared the microbiota of BA with other westernized populations (Santiago de Chile, Rosario-Argentina, United States-Human-microbiome-project, Bologna-Italy) and the Hadza population of hunter-gatherers. The unweighted UniFrac clustered together all westernized populations, leaving the hunter-gatherer population from Hadza out. In particular, Santiago de Chile’s population turns out to be the closest to BA’s, principally due to the presence of Verrucomicrobiales of the genus Akkermansia. These microorganisms have been proposed as a hallmark of a healthy gut. Finally, westernized populations showed more abundant metabolism related KEEG pathways than hunter-gatherers, including carbohydrate metabolism (amino sugar and nucleotide sugar metabolism), amino acid metabolism (alanine, aspartate and glutamate metabolism), lipid metabolism, biosynthesis of secondary metabolites, and sulfur metabolism. These findings contribute to promote research and comparison of the microbiome in different human populations, in order to develop more efficient therapeutic strategies for the restoration of a healthy dialogue between host and environment.

Culture-independent studies on bacterial dysbiosis in oral and oropharyngeal squamous cell carcinoma: A systematic review

Imbalance within the resident bacterial community (dysbiosis), rather than the presence and activity of a single organism, has been proposed to be associated with, and to influence, the development and progression of various diseases; however, the existence and significance of dysbiosis in oral/oropharyngeal cancer is yet to be clearly established. A systematic search (conducted on 25/01/2018 and updated on 25/05/2018) was performed on three databases (Pubmed, Web of Science & Scopus) to identify studies employing culture-independent methods which investigated the bacterial community in oral/oropharyngeal cancer patients compared to control subjects. Of the 1546 texts screened, only fifteen publications met the pre-determined selection criteria. Data extracted from 731 cases and 809 controls overall, could not identify consistent enrichment of any particular taxon in oral/oropharyngeal cancers, although common taxa could be identified between studies. Six studies reported the enrichment of Fusobacteria in cancer at different taxonomic levels whereas four studies reported an increase in Parvimonas. Changes in microbial diversity remained inconclusive, with four studies showing a higher diversity in controls, three studies showing a higher diversity in tumors and three additional studies showing no difference between tumors and controls. Even though most studies identified a component of dysbiosis in oral/oropharyngeal cancer, methodological and analytical variations prevented a standardized summary, which highlights the necessity for studies of superior quality and magnitude employing standardized methodology and reporting. Indeed an holistic metagenomic approach is likely to be more meaningful, as is understanding of the overall metabolome, rather than a mere enumeration of the organisms present.

Extreme value analysis of gut microbial alterations in colorectal cancer

Gut microbes play a key role in colorectal carcinogenesis, yet reaching a consensus on microbial signatures remains a challenge. This is in part due to a reliance on mean value estimates. We present an extreme value analysis for overcoming these limitations. By characterizing a power-law fit to the relative abundances of microbes, we capture the same microbial signatures as more complex meta-analyses. Importantly, we show that our method is robust to the variations inherent in microbial community profiling and point to future directions for developing sensitive, reliable analytical methods.

Rapidly Processed Stool Swabs Approximate Stool Microbiota Profiles

Studies of the intestinal microbiome commonly utilize stool samples to measure the microbial composition in the distal gut. However, collection of stool can be difficult from some subjects under certain experimental conditions. Sampling of fecal material using sterile swabs can streamline sample collection, handling, and processing. In this study, we validate the use of swabs of fecal matter to approximate measurements of microbiota in stool using 16S rRNA gene Illumina amplicon sequencing and evaluate the effects of shipping time at ambient temperatures on accuracy. The results indicate that swab samples reliably replicate the stool microbiota bacterial composition, alpha diversity, and beta diversity when swabs are processed quickly (≤2 days) but that sample quality quickly degrades after this period and is accompanied by increased abundances of Enterobacteriaceae Fresh swabs appear to be a viable alternative to stool sampling when standard collection methods are challenging, but extended exposure to ambient temperatures prior to processing threatens sample integrity.IMPORTANCE Collection of fecal swab samples simplifies handling, processing, and archiving compared to collection of stool. This study confirms that fecal swabs reliably replicate the bacterial composition and diversity of stool samples, provided that the swabs are processed shortly after collection. These findings support the use of fecal swabs, when shipping and handling are done properly, to streamline measurements of intestinal microbiota.

The human microbiome in health and disease: hype or hope

OBJECTIVES

The prognostic, diagnostic, and therapeutic potential of the human gut microbiota is widely recognised. However, translation of microbiome findings to clinical practice is challenging. Here, we discuss current knowledge and applications in the field.

METHODS

We revisit some recent advances in the field of faecal microbiome analyses with a focus on covariate analyses and ecological interpretation.

RESULTS

Population-level characterization of gut microbiota variation among healthy volunteers has allowed identifying microbiome covariates required for clinical studies. Currently, microbiome research is moving from relative to quantitative approaches that will shed a new light on microbiota-host interactions in health and disease.

CONCLUSIONS

Covariate characterization and technical advances increase reproducibility of microbiome research. Targeted in vitro/in vivo intervention studies will accelerate clinical implementation of microbiota findings.

A comparison of storage methods for gut microbiome studies in teleosts: Insights from rainbow trout (Oncorhynchus mykiss)

Immediate freezing is perhaps the most preferred method used for preserving gut microbial samples, but research on sample preservation has been principally based around samples from mammalian species, and little is known about the advantages or disadvantages relating to different storage methods for fish guts. Fish gut samples may pose additional challenges due to the different chemical and enzymatic profile, as well as the higher water content, which might affect the yield and purity of DNA recovered. To explore this, we took gut content and mucosal scrape samples from 10 rainbow trout (Oncorhynchus mykiss), and tested whether different preservation methods have any effect on the ability to construct high quality genomic libraries for shotgun and 16S rRNA gene sequencing. Four different storage methods were compared for the gut content samples (immediate freezing on dry ice, 96% ethanol, RNAlater and DNA/RNA shield), while two different methods were compared for mucosal scrape samples (96% ethanol and RNAlater). The samples were thereafter stored at -80 °C. Our findings concluded that 96% ethanol outperforms the other storage methods when considering DNA quantity, quality, cost and labor. Ethanol works consistently well for both gut content and mucosal scrape samples, and enables construction of DNA sequencing libraries of sufficient quantity and with a fragment length distribution suitable for shotgun sequencing. Two main conclusions from our study are i) sample storage optimisation is an important part of establishing a microbiome research program in a new species or sample type system, and ii) 96% ethanol is the preferred method for storing rainbow trout gut content and mucosal scrape samples.

Effects of the long-term storage of human fecal microbiota samples collected in RNAlater

The adequate storage of fecal samples from clinical trials is crucial if analyses are to be performed later and in long-term studies. However, it is unknown whether the composition of the microbiota is preserved during long-term stool storage (>1 year). We therefore evaluated the influence of long-term storage on the microbiota composition of human stool samples collected in RNAlater and stored for approximately five years at −80 °C. We compared storage effects on stool samples from 24 subjects with the effects of technical variation due to different sequencing runs and biological variation (intra- and inter-subject), in another 101 subjects, based on alpha-diversity, beta-diversity and taxonomic composition. We also evaluated the impact of initial alpha-diversity and fecal microbiota composition on beta-diversity instability upon storage. Overall, long-term stool storage at −80 °C had only limited effects on the microbiota composition of human feces. The magnitude of changes in alpha- and beta- diversity and taxonomic composition after long-term storage was similar to inter-sequencing variation and smaller than biological variation (both intra- and inter-subject). The likelihood of fecal samples being affected by long-term storage correlated with the initial relative abundance of some genera and tend to be affected by initial taxonomic richness.

Impact of inter- and intra-individual variation, sample storage and sampling fraction on human stool microbial community profiles

Stools are commonly used as proxies for studying human gut microbial communities as sample collection is straightforward, cheap and non-invasive. In large-scale human population surveys, however, sample integrity becomes an issue as it is not logistically feasible for researchers to personally collect stools from every participant. Instead, participants are usually given guidelines on sample packaging and storage, and asked to deliver their stools to a centralised facility. Here, we tested a number of delivery conditions (temperature, duration and addition of preservative medium) and assessed their effects on stool microbial community composition using 16S rRNA gene amplicon sequencing. The largest source of variability in stool community composition was attributable to inter-individual differences regardless of delivery condition. Although the relative effect of delivery condition on community composition was small compared to inter-individual variability (1.6% vs. 60.5%, permutational multivariate analysis of variance [PERMANOVA]) and temporal variation within subjects over 10 weeks (5.2%), shifts in microbial taxa associated with delivery conditions were non-systematic and subject-specific. These findings indicated that it is not possible to model or accurately predict shifts in stool community composition associated with sampling logistics. Based on our findings, we recommend delivery of fresh, preservative-free stool samples to laboratories within 2 hr either at ambient or chilled temperatures to minimise perturbations to microbial community composition. In addition, subsamples from different fractions of the same stool displayed a small (3.3% vs. 72.6% inter-individual variation, PERMANOVA) but significant effect on community composition. Collection of larger sample volumes for homogenisation is recommended.

Impact of Preservation Method and 16S rRNA Hypervariable Region on Gut Microbiota Profiling

Proper preservation of stool samples to minimize microbial community shifts and inactivate infectious agents is important for self-collected specimens requiring shipment to laboratories when cold chain transport is not feasible. In this study, we evaluated the performance of six preservation solutions (Norgen, OMNI, RNAlater, CURNA, HEMA, and Shield) for these aspects. Following storage of human stool samples with these preservatives at room temperature for 7 days, three hypervariable regions of the bacterial 16S rRNA gene (V1-V2, V3-V4, and V4) were amplicon sequenced. We found that samples collected in two preservatives, Norgen and OMNI, showed the least shift in community composition relative to -80°C standards compared with other storage conditions, and both efficiently inhibited the growth of aerobic and anaerobic bacteria. RNAlater did not prevent bacterial activity and exhibited relatively larger community shift. Although the effect of preservation solution was small compared to intersubject variation, notable changes in microbiota composition were observed, which could create biases in downstream data analysis. When community profiles inferred from different 16S rRNA gene hypervariable regions were compared, we found differential sensitivity of primer sets in identifying overall microbial community and certain bacterial taxa. For example, reads generated by the V4 primer pair showed a higher alpha diversity of the gut microbial community. The degenerate 27f-YM primer failed to detect the majority of Bifidobacteriales. Our data indicate that choice of preservation solution and 16S rRNA gene primer pair are critical determinants affecting gut microbiota profiling. IMPORTANCE Large-scale human microbiota studies require specimens collected from multiple sites and/or time points to maximize detection of the small effects in microbe-host interactions. However, batch biases caused by experimental protocols, such as sample collection, massively parallel sequencing, and bioinformatics analyses, remain critical and should be minimized. This work evaluated the effects of preservation solutions and bacterial 16S rRNA gene primer pairs in revealing human gut microbiota composition. Since notable changes in detecting bacterial composition and abundance were observed among choice of preservatives and primer pairs, a consistent methodology is essential in minimizing their effects to facilitate comparisons between data sets.

Comparison of Oral Collection Methods for Studies of Microbiota

BACKGROUND

A number of cohort studies have collected Scope mouthwash samples by mail, which are being used for microbiota measurements. We evaluated the stability of Scope mouthwash samples at ambient temperature and determined the comparability of Scope mouthwash with saliva collection using the OMNIgene ORAL Kit.

METHODS

Fifty-three healthy volunteers from Mayo Clinic and 50 cohort members from Bangladesh provided oral samples. One aliquot of the OMNIgene ORAL and Scope mouthwash were frozen immediately and one aliquot of the Scope mouthwash remained at ambient temperature for 4 days and was then frozen. DNA was extracted and the V4 region of the 16S rRNA gene was PCR amplified and sequenced using the HiSeq. Intraclass correlation coefficients (ICC) were calculated.

RESULTS

The overall stability of the Scope mouthwash samples was relatively high for alpha and beta diversity. For example, the meta-analyzed ICC for the Shannon index was 0.86 (95% confidence interval, 0.76-0.96). Similarly, the ICCs for the relative abundance of the top 25 genera were generally high. The comparability of the two sample types was relatively low when measured using ICCs, but were increased by using a Spearman correlation coefficient (SCC) to compare the rank order of individuals.

CONCLUSIONS

Overall, the Scope mouthwash samples appear to be stable at ambient temperature, which suggests that oral rinse samples received by the mail can be used for microbial analyses. However, Scope mouthwash samples were distinct compared with OMNIgene ORAL samples.

IMPACT

Studies should try to compare oral microbial metrics within one sample collection type.

Microbiome 101: Studying, Analyzing, and Interpreting Gut Microbiome Data for Clinicians

Advances in technical capabilities for reading complex human microbiomes are leading to an explosion of microbiome research, leading in turn to intense interest among clinicians in applying these techniques to their patients. In this review, we discuss the content of the human microbiome, including intersubject and intrasubject variability, considerations of study design including important confounding factors, and different methods in the laboratory and on the computer to read the microbiome and its resulting gene products and metabolites. We highlight several common pitfalls for clinicians, including the expectation that an individual's microbiome will be stable, that diet can induce rapid changes that are large compared with the differences among subjects, that everyone has essentially the same core stool microbiome, and that different laboratory and computational methods will yield essentially the same results. We also highlight the current limitations and future promise of these techniques, with the expectation that an understanding of these considerations will help accelerate the path toward routine clinical application of these techniques developed in research settings.

Methods for Studying Gut Microbiota: A Primer for Physicians

Human gastrointestinal tract contains a large variety of microbes, in particular bacteria. Studies in recent years have strongly suggested a role for these microbes, collectively referred to as gut microbiota, in the maintenance of homeostasis during health. In addition, alterations in gut microbiota have been reported in several diseases, including those related to the gastrointestinal tract and several systemic conditions, and are believed to play a pathogenetic role in at least some of these. Given the close association between the human gut and liver, the association with gut microbiota appears to be particularly strong for a wide variety of liver diseases. This piece, aimed primarily at physicians, reviews in brief the methods used to study gut microbiota, with particular emphasis on those that use sequences of bacterial 16S rRNA gene or its components.

Hybrid-denovo: a de novo OTU-picking pipeline integrating single-end and paired-end 16S sequence tags

Background

Illumina paired-end sequencing has been increasingly popular for 16S rRNA gene-based microbiota profiling. It provides higher phylogenetic resolution than single-end reads due to a longer read length. However, the reverse read (R2) often has significant low base quality, and a large proportion of R2s will be discarded after quality control, resulting in a mixture of paired-end and single-end reads. A typical 16S analysis pipeline usually processes either paired-end or single-end reads but not a mixture. Thus, the quantification accuracy and statistical power will be reduced due to the loss of a large amount of reads. As a result, rare taxa may not be detectable with the paired-end approach, or low taxonomic resolution will result in a single-end approach.

Results

To have both the higher phylogenetic resolution provided by paired-end reads and the higher sequence coverage by single-end reads, we propose a novel OTU-picking pipeline, hybrid-denovo, that can process a hybrid of single-end and paired-end reads. Using high-quality paired-end reads as a gold standard, we show that hybrid-denovo achieved the highest correlation with the gold standard and performed better than the approaches based on paired-end or single-end reads in terms of quantifying the microbial diversity and taxonomic abundances. By applying our method to a rheumatoid arthritis (RA) data set, we demonstrated that hybrid-denovo captured more microbial diversity and identified more RA-associated taxa than a paired-end or single-end approach.

Conclusions

Hybrid-denovo utilizes both paired-end and single-end 16S sequencing reads and is recommended for 16S rRNA gene targeted paired-end sequencing data.

Next steps in studying the human microbiome and health in prospective studies, Bethesda, MD, May 16-17, 2017

The National Cancer Institute (NCI) sponsored a 2-day workshop, "Next Steps in Studying the Human Microbiome and Health in Prospective Studies," in Bethesda, Maryland, May 16-17, 2017. The workshop brought together researchers in the field to discuss the challenges of conducting microbiome studies, including study design, collection and processing of samples, bioinformatics and statistical methods, publishing results, and ensuring reproducibility of published results. The presenters emphasized the great potential of microbiome research in understanding the etiology of cancer. This report summarizes the workshop and presents practical suggestions for conducting microbiome studies, from workshop presenters, moderators, and participants.

Interpersonal Variations in Gut Microbiota Profiles Supersedes the Effects of Differing Fecal Storage Conditions

Due to ease of acquisition, fecal samples are often used in studies investigating gut microbiota. Improper handling of these samples can lead to bacterial growth and alter bacterial composition. While freezing samples at −80 °C is considered gold standard, this is not suitable for studies utilizing self-sampling by lay participants or field studies. Thus to effectively prevent bacterial growth, techniques that allow efficient fecal storage outside laboratory facilities are needed. Fecal samples were collected from three donors. From each donor feces, 45 samples were collected and stored either freshly frozen at −80 or −20 °C, or in three separate storage buffers at room temperature or 4 °C for 24 or 72 hours. Bacterial composition was analyzed using Illumina amplicon sequencing of the V4 region of the 16 S rRNA gene. While storage conditions did affect bacterial composition and diversity compared to storage at −80 °C, the variation between donors superseded the variations introduced by storage. Samples stored at −20 °C most closely resembled those stored at −80 °C. When investigating variations in bacterial composition between separate study populations, fecal samples can efficiently be stored in −20 °C freezers or in one of the presented storage buffers, without severe alterations in bacterial composition.

Evaluating gut microbiota profiles from archived fecal samples

BACKGROUND

Associations between colorectal cancer and microbiota have been identified. Archived fecal samples might be valuable sample sources for investigating causality in carcinogenesis and biomarkers discovery due to the potential of performing longitudinal studies. However, the quality, quantity and stability of the gut microbiota in these fecal samples must be assessed prior to such studies. We evaluated i) cross-contamination during analysis for fecal blood and ii) evaporation in stored perforated fecal immunochemical tests (iFOBT) samples, iii) temperature stability as well as iv) comparison of the gut microbiota diversity and composition in archived, iFOBT and fresh fecal samples in order to assess feasibility of large scale microbiota studies.

METHODS

The microbiota profiles were obtained by sequencing the V3-V4 region of 16S rDNA gene.

RESULTS

The iFOBT does not introduce any cross-sample contamination detectable by qPCR. Neither could we detect evaporation during freeze-thaw cycle of perforated iFOBT samples. Our results confirm room temperature stability of the gut microbiome. Diverse microbial profiles were achieved in 100% of fresh, 81% of long-term archived and 96% of iFOBT samples. Microbial diversity and composition were comparable between fresh and iFOBT samples, however, diversity differed significantly between long-term archived, fresh and iFOBT samples.

CONCLUSION

Our data showed that it is feasible to exploit archived fecal sample sets originally collected for testing of fecal blood. The advantages of using these sample sets for microbial biomarker discovery and longitudinal observational studies are the availability of high-quality diagnostic and follow-up data. However, care must be taken when microbiota are profiled in long-term archived fecal samples.

Nutrimetabolomics: An Integrative Action for Metabolomic Analyses in Human Nutritional Studies

The life sciences are currently being transformed by an unprecedented wave of developments in molecular analysis, which include important advances in instrumental analysis as well as biocomputing. In light of the central role played by metabolism in nutrition, metabolomics is rapidly being established as a key analytical tool in human nutritional studies. Consequently, an increasing number of nutritionists integrate metabolomics into their study designs. Within this dynamic landscape, the potential of nutritional metabolomics (nutrimetabolomics) to be translated into a science, which can impact on health policies, still needs to be realized. A key element to reach this goal is the ability of the research community to join, to collectively make the best use of the potential offered by nutritional metabolomics. This article, therefore, provides a methodological description of nutritional metabolomics that reflects on the state-of-the-art techniques used in the laboratories of the Food Biomarker Alliance (funded by the European Joint Programming Initiative "A Healthy Diet for a Healthy Life" (JPI HDHL)) as well as points of reflections to harmonize this field. It is not intended to be exhaustive but rather to present a pragmatic guidance on metabolomic methodologies, providing readers with useful "tips and tricks" along the analytical workflow.

Conducting metagenomic studies in microbiology and clinical research

Owing to the increased cost-effectiveness of high-throughput technologies, the number of studies focusing on the human microbiome and its connections to human health and disease has recently surged. However, best practices in microbiology and clinical research have yet to be clearly established. Here, we present an overview of the challenges and opportunities involved in conducting a metagenomic study, with a particular focus on data processing and analytical methods.

Temporal Variability and Stability of the Fecal Microbiome: The Multiethnic Cohort Study

BACKGROUND

Measurement reliability and biological stability need to be considered when developing sampling protocols for population-based fecal microbiome studies.

METHODS

Stool samples were collected biannually over a 2-year period and sequenced for the V1-V3 region of the 16S rRNA gene in 50 participants from the Multiethnic Cohort Study. We evaluated the temporal stability of the fecal microbiome on a community level with permutational multivariate analysis of variance (PERMANOVA), as well as on taxa and diversity measures with intraclass correlation coefficients.

RESULTS

Interindividual differences were the predominant source of fecal microbiome variation, and variation within individual was driven more by changing abundances than by the complete loss or introduction of taxa. Phyla and diversity measures were reliable over the 2 years. Most genera were stable over time, although those with low abundances tended to be more dynamic. Reliability was lower among participants who used antibiotics, with the greatest difference seen in samples taken within 1 month of reported use.

CONCLUSIONS

The fecal microbiome as a whole is stable over a 2-year period, although certain taxa may exhibit more temporal variability.

IMPACT

When designing large epidemiologic studies, a single sample is sufficient to capture the majority of the variation in the fecal microbiome from 16S rRNA gene sequencing, while multiple samples may be needed for rare or less-abundant taxa.

Comparison of Fecal Collection Methods for Microbiome and Metabolomics Studies

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.

Combined bacterial and fungal intestinal microbiota analyses: Impact of storage conditions and DNA extraction protocols

Background

The human intestinal microbiota contains a vast community of microorganisms increasingly studied using high-throughput DNA sequencing. Standardized protocols for storage and DNA extraction from fecal samples have been established mostly for bacterial microbiota analysis. Here, we investigated the impact of storage and DNA extraction on bacterial and fungal community structures detected concomitantly.

Methods

Fecal samples from healthy adults were stored at -80°C as such or diluted in RNAlater® and subjected to 2 extraction protocols with mechanical lysis: the Powersoil® MoBio kit or the International Human Microbiota Standard (IHMS) Protocol Q. Libraries of the 12 samples targeting the V3-V4 16S and the ITS1 regions were prepared using Metabiote® (Genoscreen) and sequenced on GS-FLX-454. Sequencing data were analysed using SHAMAN (http://shaman.pasteur.fr/). The bacterial and fungal microbiota were compared in terms of diversity and relative abundance.

Results

We obtained 171869 and 199089 quality-controlled reads for 16S and ITS, respectively. All 16S reads were assigned to 41 bacterial genera; only 52% of ITS reads were assigned to 40 fungal genera/section. Rarefaction curves were satisfactory in 3/3 and 2/3 subjects for 16S and ITS, respectively. PCoA showed important inter-individual variability of intestinal microbiota largely overweighing the effect of storage or extraction. Storage in RNAlater® impacted (downward trend) the relative abundances of 7/41 bacterial and 6/40 fungal taxa, while extraction impacted randomly 18/41 bacterial taxa and 1/40 fungal taxon.

Conclusion

Our results showed that RNAlater® moderately impacts bacterial or fungal community structures, while extraction significantly influences the bacterial composition. For combined bacterial and fungal intestinal microbiota analysis, immediate sample freezing should be preferred when feasible, but storage in RNAlater® remains an option under unfavourable conditions or for concomitant metatranscriptomic analysis; and extraction should rely on protocols validated for bacterial analysis, such as IHMS Protocol Q, and including a powerful mechanical lysis, essential for fungal extraction.

A taxonomic signature of obesity in a large study of American adults

Animal models suggest that gut microbiota contribute to obesity; however, a consistent taxonomic signature of obesity has yet to be identified in humans. We examined whether a taxonomic signature of obesity is present across two independent study populations. We assessed gut microbiome from stool for 599 adults, by 16S rRNA gene sequencing. We compared gut microbiome diversity, overall composition, and individual taxon abundance for obese (BMI ≥ 30 kg/m2), overweight (25 ≤ BMI < 30), and healthy-weight participants (18.5 ≤ BMI < 25). We found that gut species richness was reduced (p = 0.04), and overall composition altered (p = 0.04), in obese (but not overweight) compared to healthy-weight participants. Obesity was characterized by increased abundance of class Bacilli and its families Streptococcaceae and Lactobacillaceae, and decreased abundance of several groups within class Clostridia, including Christensenellaceae, Clostridiaceae, and Dehalobacteriaceae (q < 0.05). These findings were consistent across two independent study populations. When random forest models were trained on one population and tested on the other as well as a previously published dataset, accuracy of obesity prediction was good (~70%). Our large study identified a strong and consistent taxonomic signature of obesity. Though our study is cross-sectional and causality cannot be determined, identification of microbes associated with obesity can potentially provide targets for obesity prevention and treatment.

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.