Comparison of Fecal Collection Methods for Microbiota Studies in Bangladesh

Effectiveness of stabilization methods for the immediate and short-term preservation of bovine fecal and upper respiratory tract genomic DNA

Previous research on stabilization methods for microbiome investigations has largely focused on human fecal samples. There are a few studies using feces from other species, but no published studies investigating preservation of samples collected from cattle. Given that microbial taxa are differentially impacted during storage it is warranted to study impacts of preservation methods on microbial communities found in samples outside of human fecal samples. Here we tested methods of preserving bovine fecal respiratory specimens for up to 2 weeks at four temperatures (room temperature, 4°C, -20°C, and -80°C) by comparing microbial diversity and community composition to samples extracted immediately after collection. Importantly, fecal specimens preserved and analyzed were technical replicates, providing a look at the effects of preservation method in the absence of biological variation. We found that preservation with the OMNIgene®•GUT kit resulted in community structure most like that of fresh samples extracted immediately, even when stored at room temperature (~20°C). Samples that were flash-frozen without added preservation solution were the next most representative of original communities, while samples preserved with ethanol were the least representative. These results contradict previous reports that ethanol is effective in preserving fecal communities and suggest for studies investigating cattle either flash-freezing of samples without preservative or preservation with OMNIgene®•GUT will yield more representative microbial communities.

Techniques, procedures, and applications in microbiome analysis

Microbiota is a complex community of microorganisms living in a defined environment. Until the 20th century, knowledge of microbiota was partial, as the techniques available for their characterization were primarily based on bacteriological culture. In the last twenty years, the development of DNA sequencing technologies, multi-omics, and bioinformatics has expanded our understanding of microorganisms. We have moved from mainly considering them isolated disease-causing agents to recognizing the microbiota as an essential component of host biology. These techniques have shown that the microbiome plays essential roles in various host phenotypes, influencing development, physiology, reproduction, and evolution. This chapter provides researchers with a summary of the primary concepts, sample collection, experimental techniques, and bioinformatics analysis commonly used in microbiome research. The main features, applications in microbiome studies, and their advantages and limitations are included in each section.

A gut microbiome signature for HIV and metabolic dysfunction-associated steatotic liver disease

Introduction

Metabolic dysfunction-associated steatotic liver disease (MASLD), has emerged as an increasingly recognized problem among people living with HIV (PLWH). The gut-liver axis is considered to be strongly implicated in the pathogenesis of MASLD. We aimed to characterize the gut microbiota composition in PLWH and MASLD and compare it with that of two control groups: PLWH without MASLD and individuals with MASLD without HIV infection.

Methods

We collected clinical data and stool samples from participants. Bacterial 16S rRNA genes were amplified, sequenced, and clustered into operational taxonomic unit. Alpha diversity was studied by Shannon and Simpson indexes. To study how different the gut microbiota composition is between the different groups, beta diversity estimation was evaluated by principal coordinate analysis (PCoA) using Bray-Curtis dissimilarity. To further analyze differences in microbiome composition we performed a linear discriminant analysis (LDA) effect size (LEfSe).

Results

We included 30 HIV+MASLD+, 30 HIV+MASLD- and 20 HIV-MASLD+ participants. Major butyrate producers, including Faecalibacterium, Ruminococcus, and Lachnospira dominated the microbiota in all three groups. Shannon's and Simpson's diversity metrics were higher among MASLD+ individuals (Kruskal-Wallis p = 0.047). Beta diversity analysis showed distinct clustering in MASLD-, with MASLD+ participants overlapping regardless of HIV status (ADONIS significance <0.001). MASLD was associated with increased homogeneity across individuals, in contrast to that observed in the HIV+NAFDL- group, in which the dispersion was higher (Permanova test, p value <0.001; ANOSIM, p value <0.001). MASLD but not HIV determined a different microbiota structure (HIV+MASLD- vs. HIV+MASLD+, q-value = 0.002; HIV-MASLD+ vs. HIV+MASLD+, q-value = 0.930; and HIV-MASLD+ vs. HIV+MASLD-, q-value < 0.001). The most abundant genera in MASLD- were Prevotella, Bacteroides, Dialister, Acidaminococcos, Alloprevotella, and Catenibacterium. In contrast, the most enriched genera in MASLD+ were Ruminococcus, Streptococcus, Holdemanella, Blautia, and Lactobacillus.

Conclusions

We found a microbiome signature linked to MASLD, which had a greater influence on the overall structure of the gut microbiota than HIV status alone.

Methods in Nutrition & Gut Microbiome Research: An American Society for Nutrition Satellite Session [13 October 2022]

The microbial cells colonizing the human body form an ecosystem that is integral to the regulation and maintenance of human health. Elucidation of specific associations between the human microbiome and health outcomes is facilitating the development of microbiome-targeted recommendations and treatments (e.g., fecal microbiota transplant; pre-, pro-, and post-biotics) to help prevent and treat disease. However, the potential of such recommendations and treatments to improve human health has yet to be fully realized. Technological advances have led to the development and proliferation of a wide range of tools and methods to collect, store, sequence, and analyze microbiome samples. However, differences in methodology at each step in these analytic processes can lead to variability in results due to the unique biases and limitations of each component. This technical variability hampers the detection and validation of associations with small to medium effect sizes. Therefore, the American Society for Nutrition (ASN) Nutritional Microbiology Group Engaging Members (GEM), sponsored by the Institute for the Advancement of Food and Nutrition Sciences (IAFNS), hosted a satellite session on methods in nutrition and gut microbiome research to review currently available methods for microbiome research, best practices, as well as tools and standards to aid in comparability of methods and results. This manuscript summarizes the topics and research discussed at the session. Consideration of the guidelines and principles reviewed in this session will increase the accuracy, precision, and comparability of microbiome research and ultimately the understanding of the associations between the human microbiome and health.

Stability of the Fecal and Oral Microbiome over 2 Years at -80°C for Multiple Collection Methods

BACKGROUND

In prospective cohorts, biological samples are generally stored over long periods before an adequate number of cases have accrued. We investigated the impact of sample storage at -80°C for 2 years on the stability of the V4 region of the 16S rRNA gene across seven different collection methods (i.e., no additive, 95% ethanol, RNAlater stabilization solution, fecal occult blood test cards, and fecal immunochemical test tubes for feces; OMNIgene ORAL tubes and Scope mouthwash for saliva) among 51 healthy volunteers.

METHODS

Intraclass correlation coefficients (ICC) were calculated for the relative abundance of the top three phyla, the 20 most abundant genera, three alpha-diversity metrics, and the first principal coordinates of three beta-diversity matrices.

RESULTS

The subject variability was much higher than the variability introduced by the sample collection type, and storage time. For fecal samples, microbial stability over 2 years was high across collection methods (range, ICCs = 0.70-0.99), except for the samples collected with no additive (range, ICCs = 0.23-0.83). For oral samples, most microbiome diversity measures were stable over time with ICCs above 0.74; however, ICCs for the samples collected with Scope mouthwash were lower for two alpha-diversity measures, Faith's phylogenetic diversity (0.23) and the observed number of operational taxonomic units (0.23).

CONCLUSIONS

Fecal and oral samples in most used collection methods are stable for microbiome analyses after 2 years at -80°C, except for fecal samples with no additive.

IMPACT

This study provides evidence that samples stored for an extended period from prospective studies are useful for microbiome analyses.

Using fecal immmunochemical cartridges for gut microbiome analysis within a colorectal cancer screening program

The colorectal cancer (CRC) screening program B-PREDICT is an invited two-stage screening project using a fecal immunochemical test (FIT) for initial screening followed by a colonoscopy for those with a positive FIT. Since the gut microbiome likely plays a role in the etiology of CRC, microbiome-based biomarkers in combination with FIT could be a promising tool for optimizing CRC screening. Therefore, we evaluated the usability of FIT cartridges for microbiome analysis and compared it to Stool Collection and Preservation Tubes. Corresponding FIT cartridges as well as Stool Collection and Preservation Tubes were collected from participants of the B-PREDICT screening program to perform 16S rRNA gene sequencing. We calculated intraclass correlation coefficients (ICCs) based on center log ratio transformed abundances and used ALDEx2 to test for significantly differential abundant taxa between the two sample types. Additionally, FIT and Stool Collection and Preservation Tube triplicate samples were obtained from volunteers to estimate variance components of microbial abundances. FIT and Preservation Tube samples produce highly similar microbiome profiles which cluster according to subject. Significant differences between the two sample types can be found for abundances of some bacterial taxa (e.g. 33 genera) but are minor compared to the differences between the subjects. Analysis of triplicate samples revealed slightly worse repeatability of results for FIT than for Preservation Tube samples. Our findings indicate that FIT cartridges are appropriate for gut microbiome analysis nested within CRC screening programs.

dICC: distance-based intraclass correlation coefficient for metagenomic reproducibility studies

SUMMARY

Due to the sparsity and high dimensionality, microbiome data are routinely summarized into pairwise distances capturing the compositional differences. Many biological insights can be gained by analyzing the distance matrix in relation to some covariates. A microbiome sampling method that characterizes the inter-sample relationship more reproducibly is expected to yield higher statistical power. Traditionally, the intraclass correlation coefficient (ICC) has been used to quantify the degree of reproducibility for a univariate measurement using technical replicates. In this work, we extend the traditional ICC to distance measures and propose a distance-based ICC (dICC). We derive the asymptotic distribution of the sample-based dICC to facilitate statistical inference. We illustrate dICC using a real dataset from a metagenomic reproducibility study.

AVAILABILITY AND IMPLEMENTATION

dICC is implemented in the R CRAN package GUniFrac.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Reusing a prepaid health plan's fecal immunochemical tests for microbiome associations with colorectal adenoma

An altered colonic microbiota probably increases colorectal adenoma (CRA) and cancer (CRC) risk, but large, unbiased fecal collections are needed to examine the relationship of gut microbiota diversity and composition to colorectal carcinogenesis. This study assessed whether fecal immunochemical tests (FITs) from CRA/CRC screening may fulfill this requirement. Using FIT, self-collected by members of Kaiser Permanente Hawaii (KPH), as well as interspersed quality control (QC) specimens, DNA was extracted and amplified to generate 16S rRNA microbiome profiles rarified at 10,000 reads. CRA/CRC were diagnosed by colonoscopy and histopathology. Covariates were from electronic KPH records. Of 921 participants’ FIT devices, 538 (58%) yielded at least 10,000 rRNA reads and 1016 species-level variants mapped to 46 genera. Of the 538 evaluable participants, 63 (11.7%) were FIT-negative per protocol, and they were considered negative for CRA/CRC. Of the 475 FIT + participants, colonoscopy and pathologic review revealed that 8 (1.7%) had CRC, 71 (14.9%) had high-risk CRA, 107 (22.5%) had low-risk CRA, and 289 (60.8%) did not have CRA/CRC. Men were 2.27-fold [95% confidence interval (CI) 1.32–3.91] more likely than women to be FIT+ . Men also had 1.96-fold (CI 1.24–3.07) higher odds of low-risk CRA, with similar trends for high-risk CRA and CRC. CRA/CRC were not associated with overweight, obesity, diabetes, or antibiotic prescriptions in this study. QC analysis across 24 batches of FIT devices revealed QC outliers in four batches. With or without exclusion of the four QC-outlier batches, as well as lenient (1000-read) rarefaction, CRA/CRC had no consistent, statistically significant associations with fecal microbiome alpha diversity, beta diversity or genera relative abundance. CRA/CRC had expected associations with male sex but not with microbiome metrics. Fecal microbiome profiling using DNA extracted from at-home collected, re-used FIT devices is feasible, albeit with substantial challenges. Using FITs for prospective microbiome studies of CRA/CRC risk should consider the impact of the current findings on statistical power and requisite sample sizes.

Habitual Diet Pattern Associations with Gut Microbiome Diversity and Composition: Results from a Chinese Adult Cohort

The influence of long-term diet on gut microbiota is an active area of investigation. The present work aimed to explore the associations between habitual diet patterns and gut microbiota in a large sample of asymptomatic Chinese adults. The gut microbiome was profiled through the sequencing of the 16S rRNA gene in stool samples from 702 Chinese adults aged 50–75 years who underwent colonoscopies and were diagnosed to be free of colorectal neoplasm. Long-term dietary consumption was assessed through a food-frequency questionnaire. The microbial associations with specific food groups and the posteriori dietary pattern were tested using the Kruskal–Wallis H test, permutational ANOVAs, and multivariate analyses with linear models. The Shannon indexes generally shared similar levels across different food intake frequency groups. Whole grain and vegetable intakes totally explained 1.46% of the microbiota compositional variance. Using the data-driven posteriori approach, a general dietary pattern characterized by lower intakes of refined grains was highlighted to be associated with higher abundances of the genus Anaerostipes and a species of it. We also observed 17 associations between various food group intakes and specific genera and species. For instance, the relative abundances of the genus Weissella and an uncultured species of it were negatively associated with red meat intake. The results of this study support the idea that the usual dietary consumption measured by certain food items or summary indexes is associated with gut microbial features. These results deepen the understanding of complex relationships of diet and gut microbiota, as well as their implications for gut microbiome studies of human chronic diseases.

Comparative evaluation of fish larval preservation methods on microbiome profiles to aid in metagenomics research

Applications of microbiome research through metagenomics promise to generate microbiome manipulation strategies for improved larval survival in aquaculture. However, existing lacunae on the effects of sample preservation methods in metagenome profiles hinder the successful application of this technique. In this context, four preservation methods were scrutinized to identify reliable methods for fish larval microbiome research. The results showed that a total of ten metagenomics metrics, including DNA yield, taxonomic and functional microbiome profiles, and diversity measures, were significantly (P < 0.05) influenced by the preservation method. Activity ranking based on the performance and reproducibility showed that three methods, namely immediate direct freezing, room temperature preservation in absolute ethanol, and preservation at - 20 °C in lysis, storage, and transportation buffer, could be recommended for larval microbiome research. Furthermore, as there was an apparent deviation of the microbiome profiles of ethanol preserved samples at room temperature, the other methods are preferred. Detailed analysis showed that this deviation was due to the bias towards Vibrionales and Rhodobacterales. The microbial taxa responsible for the dissimilarity across different methods were identified. Altogether, the paper sheds light on the preservation protocols of fish larval microbiome research for the first time. The results can help in cross-comparison of future and past larval microbiome studies. Furthermore, this is the first report on the activity ranking of preservation methods based on metagenomics metrics. Apart from methodological perspectives, the paper provides for the first time certain insights into larval microbial profiles of Rachycentron canadum, a potential marine aquaculture species. KEY POINTS: • First report on effects of preservation methods on fish larval microbiome profiles. • First report on activity ranking of preservation methods based on metagenomics metrics. • Storage methods influenced DNA yield, taxonomic and functional microbiome profiles.

Effect of different fixatives on yield of DNA from human fecal samples

Fixation and transportation of human fecal samples is often difficult in geographically remote locations due to unavailability of options for immediate freezing. In this study effectiveness of five different chemical fixatives were evaluated on human fecal samples including for supernatant using RNAprotect Bacteria Reagent (Qiagen), 95% ethanol, acetone, TRIzol and a mixture of all these fixatives, in addition to immediate freezing. DNA was extracted from the fecal samples using QIAamp Fast Stool DNA Minikit as well as quality and yield of extracted DNA was monitored for a period of 30 days. It was found that except TRIzol, all other preservatives showed good DNA quality and yield for a period of one month based on agarose gel electrophoresis, Nanodrop and Qubit measurements. It was also found that supernatant of fecal sample fixed with RNAprotect Bacteria Reagent gave reliable DNA yield in comparison to other various fixatives. The study also revealed that quality and yield of DNA from fecal samples fixed in acetone were very promising since it is a cost-effective fixative. Overall, the study shows future applicability for downstream DNA analyses of the RNAprotect Bacteria Reagent, 95% ethanol, acetone, and a mixture of all these fixatives for fixing human fecal samples to be collected from geographically remote locations or in regions where available resources are largely limited.

Library Preparation and Sequencing Platform Introduce Bias in Metagenomic-Based Characterizations of Microbiomes

Metagenomics is increasingly used to describe microbial communities in biological specimens. Ideally, the steps involved in the processing of the biological specimens should not change the microbiome composition in a way that it could lead to false interpretations of inferred microbial community composition. Common steps in sample preparation include sample collection, storage, DNA isolation, library preparation, and DNA sequencing. Here, we assess the effect of three library preparation kits and two DNA sequencing platforms. Of the library preparation kits, one involved a PCR step (Nextera), and two were PCR free (NEXTflex and KAPA). We sequenced the libraries on Illumina HiSeq and NextSeq platforms. As example microbiomes, two pig fecal samples and two sewage samples of which aliquots were stored at different storage conditions (immediate processing and storage at -80°C) were assessed. All DNA isolations were performed in duplicate, totaling 80 samples, excluding controls. We found that both library preparation and sequencing platform had systematic effects on the inferred microbial community composition. The different sequencing platforms introduced more variation than library preparation and freezing the samples. The results highlight that all sample processing steps need to be considered when comparing studies. Standardization of sample processing is key to generating comparable data within a study, and comparisons of differently generated data, such as in a meta-analysis, should be performed cautiously. IMPORTANCE Previous research has reported effects of sample storage conditions and DNA isolation procedures on metagenomics-based microbiome composition; however, the effect of library preparation and DNA sequencing in metagenomics has not been thoroughly assessed. Here, we provide evidence that library preparation and sequencing platform introduce systematic biases in the metagenomic-based characterization of microbial communities. These findings suggest that library preparation and sequencing are important parameters to keep consistent when aiming to detect small changes in microbiome community structure. Overall, we recommend that all samples in a microbiome study are processed in the same way to limit unwanted variations that could lead to false conclusions. Furthermore, if we are to obtain a more holistic insight from microbiome data generated around the world, we will need to provide more detailed sample metadata, including information about the different sample processing procedures, together with the DNA sequencing data at the public repositories.

Human Stool Preservation Impacts Taxonomic Profiles in 16S Metagenomics Studies

Microbiotas play critical roles in human health, yet in most cases scientists lack standardized and reproducible methods from collection and preservation of samples, as well as the choice of omic analysis, up to the data processing. To date, stool sample preservation remains a source of technological bias in metagenomic sequencing, despite newly developed storage solutions. Here, we conducted a comparative study of 10 storage methods for human stool over a 14-day period of storage at fluctuating temperatures. We first compared the performance of each stabilizer with observed bacterial composition variation within the same specimen. Then, we identified the nature of the observed variations to determine which bacterial populations were more impacted by the stabilizer. We found that DNA stabilizers display various stabilizing efficacies and affect the recovered bacterial profiles thus highlighting that some solutions are more performant in preserving the true gut microbial community. Furthermore, our results showed that the bias associated with the stabilizers can be linked to the phenotypical traits of the bacterial populations present in the studied samples. Although newly developed storage solutions have improved our capacity to stabilize stool microbial content over time, they are nevertheless not devoid of biases hence requiring the implantation of standard operating procedures. Acknowledging the biases and limitations of the implemented method is key to better interpret and support true associated microbiome patterns that will then lead us towards personalized medicine, in which the microbiota profile could constitute a reliable tool for clinical practice.

Comparison of Fecal Sample Collection Methods for Microbial Analysis Embedded within Colorectal Cancer Screening Programs

BACKGROUND

Colorectal cancer screening programs with fecal sample collection may provide a platform for population-based gut microbiome disease research. We investigated sample collection and storage method impact on the accuracy and stability of the V3-V4 region of the 16S rRNA genes and bacterial quantity across seven different collection methods [i.e., no solution, two specimen collection cards, and four types of fecal immunochemical test (FIT) used in four countries] among 19 healthy volunteers.

METHODS

Intraclass correlation coefficients (ICC) were calculated for the relative abundance of the top three phyla, the most abundant genera, alpha diversity metrics, and the first principal coordinates of the beta diversity matrices to estimate the stability of microbial profiles after storage for 7 days at room temperature, 4°C or 30°C, and after screening for the presence of occult blood in the stool. In addition, accuracy was estimated for samples frozen immediately compared to samples with no solution (i.e., the putative gold standard).

RESULTS

When compared with the putative gold standard, we observed significant variation for all collection methods. However, interindividual variability was much higher than the variability introduced by the collection method. Stability ICCs were high (≥0.75) for FIT tubes that underwent colorectal cancer screening procedures. The relative abundance of Actinobacteria (0.65) was an exception and was lower for different FIT tubes stored at 30°C (range, 0.41-0.90) and room temperature (range, 0.06-0.94).

CONCLUSIONS

Paper-based collection cards and different types of FIT are acceptable tools for microbiome measurements.

IMPACT

Our findings inform on the utility of commonly used fecal sample collection methods for developing microbiome-focused cohorts nested within screening programs.

Comparison of fecal and oral collection methods for studies of the human microbiota in two Iranian cohorts

Background

To initiate fecal and oral collections in prospective cohort studies for microbial analyses, it is essential to understand how field conditions and geographic differences may impact microbial communities. This study aimed to investigate the impact of fecal and oral sample collection methods and room temperature storage on collection samples for studies of the human microbiota.

Results

We collected fecal and oral samples from participants in two Iranian cohorts located in rural Yazd (n = 46) and urban Gonbad (n = 38) and investigated room temperature stability over 4 days of fecal (RNAlater and fecal occult blood test [FOBT] cards) and comparability of fecal and oral (OMNIgene ORAL kits and Scope mouthwash) collection methods. We calculated interclass correlation coefficients (ICCs) based on 3 alpha and 4 beta diversity metrics and the relative abundance of 3 phyla. After 4 days at room temperature, fecal stability ICCs and ICCs for Scope mouthwash were generally high for all microbial metrics. Similarly, the fecal comparability ICCs for RNAlater and FOBT cards were high, ranging from 0.63 (95% CI: 0.46, 0.75) for the relative abundance of Firmicutes to 0.93 (95% CI: 0.89, 0.96) for unweighted Unifrac. Comparability ICCs for OMNIgene ORAL and Scope mouthwash were lower than fecal ICCs, ranging from 0.55 (95% CI: 0.36, 0.70) for the Shannon index to 0.79 (95% CI: 0.69, 0.86) for Bray-Curtis. Overall, RNAlater, FOBT cards and Scope mouthwash were stable up to 4 days at room temperature. Samples collected using FOBT cards were generally comparable to RNAlater while the OMNIgene ORAL were less similar to Scope mouthwash.

Conclusions

As microbiome measures for feces samples collected using RNAlater, FOBT cards and oral samples collected using Scope mouthwash were stable over four days at room temperature, these would be most appropriate for microbial analyses in these populations. However, one collection method should be consistently since each method may induce some differences.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12866-021-02387-9.

Intestinal Microbiome in Hematopoietic Stem Cell Transplantation For Autoimmune Diseases: Considerations and Perspectives on Behalf of Autoimmune Diseases Working Party (ADWP) of the EBMT

Over the past decades, hematopoietic stem cell transplantation (HSCT) has been evolving as specific treatment for patients with severe and refractory autoimmune diseases (ADs), where mechanistic studies have provided evidence for a profound immune renewal facilitating the observed beneficial responses. The intestinal microbiome plays an important role in host physiology including shaping the immune repertoire. The relationships between intestinal microbiota composition and outcomes after HSCT for hematologic diseases have been identified, particularly for predicting the mortality from infectious and non-infectious causes. Furthermore, therapeutic manipulations of the gut microbiota, such as fecal microbiota transplant (FMT), have emerged as promising therapeutic approaches for restoring the functional and anatomical integrity of the intestinal microbiota post-transplantation. Although changes in the intestinal microbiome have been linked to various ADs, studies investigating the effect of intestinal dysbiosis on HSCT outcomes for ADs are scarce and require further attention. Herein, we describe some of the landmark microbiome studies in HSCT recipients and patients with chronic ADs, and discuss the challenges and opportunities of microbiome research for diagnostic and therapeutic purposes in the context of HSCT for ADs.

Standard Sample Storage Conditions Have an Impact on Inferred Microbiome Composition and Antimicrobial Resistance Patterns

Storage of biological specimens is crucial in the life and medical sciences. Storage conditions for samples can be different for a number of reasons, and it is unclear what effect this can have on the inferred microbiome composition in metagenomics analyses. Here, we assess the effect of common storage temperatures (deep freezer, -80°C; freezer, -20°C; refrigerator, 5°C; room temperature, 22°C) and storage times (immediate sample processing, 0 h; next day, 16 h; over weekend, 64 h; longer term, 4, 8, and 12 months) as well as repeated sample freezing and thawing (2 to 4 freeze-thaw cycles). We examined two different pig feces and sewage samples, unspiked and spiked with a mock community, in triplicate, respectively, amounting to a total of 438 samples (777 Gbp; 5.1 billion reads). Storage conditions had a significant and systematic effect on the taxonomic and functional composition of microbiomes. Distinct microbial taxa and antimicrobial resistance classes were, in some situations, similarly affected across samples, while others were not, suggesting an impact of individual inherent sample characteristics. With an increasing number of freeze-thaw cycles, an increasing abundance of Firmicutes, Actinobacteria, and eukaryotic microorganisms was observed. We provide recommendations for sample storage and strongly suggest including more detailed information in the metadata together with the DNA sequencing data in public repositories to better facilitate meta-analyses and reproducibility of findings. IMPORTANCE Previous research has reported effects of DNA isolation, library preparation, and sequencing technology on metagenomics-based microbiome composition; however, the effect of biospecimen storage conditions has not been thoroughly assessed. We examined the effect of common sample storage conditions on metagenomics-based microbiome composition and found significant and, in part, systematic effects. Repeated freeze-thaw cycles could be used to improve the detection of microorganisms with more rigid cell walls, including parasites. We provide a data set that could also be used for benchmarking algorithms to identify and correct for unwanted batch effects. Overall, the findings suggest that all samples of a microbiome study should be stored in the same way. Furthermore, there is a need to mandate more detailed information about sample storage and processing be published together with DNA sequencing data at the International Nucleotide Sequence Database Collaboration (ENA/EBI, NCBI, DDBJ) or other repositories.

Standard Sample Storage Conditions Have an Impact on Inferred Microbiome Composition and Antimicrobial Resistance Patterns

Storage of biological specimens is crucial in the life and medical sciences. Storage conditions for samples can be different for a number of reasons, and it is unclear what effect this can have on the inferred microbiome composition in metagenomics analyses. Here, we assess the effect of common storage temperatures (deep freezer, -80°C; freezer, -20°C; refrigerator, 5°C; room temperature, 22°C) and storage times (immediate sample processing, 0 h; next day, 16 h; over weekend, 64 h; longer term, 4, 8, and 12 months) as well as repeated sample freezing and thawing (2 to 4 freeze-thaw cycles). We examined two different pig feces and sewage samples, unspiked and spiked with a mock community, in triplicate, respectively, amounting to a total of 438 samples (777 Gbp; 5.1 billion reads). Storage conditions had a significant and systematic effect on the taxonomic and functional composition of microbiomes. Distinct microbial taxa and antimicrobial resistance classes were, in some situations, similarly affected across samples, while others were not, suggesting an impact of individual inherent sample characteristics. With an increasing number of freeze-thaw cycles, an increasing abundance of Firmicutes, Actinobacteria, and eukaryotic microorganisms was observed. We provide recommendations for sample storage and strongly suggest including more detailed information in the metadata together with the DNA sequencing data in public repositories to better facilitate meta-analyses and reproducibility of findings. IMPORTANCE Previous research has reported effects of DNA isolation, library preparation, and sequencing technology on metagenomics-based microbiome composition; however, the effect of biospecimen storage conditions has not been thoroughly assessed. We examined the effect of common sample storage conditions on metagenomics-based microbiome composition and found significant and, in part, systematic effects. Repeated freeze-thaw cycles could be used to improve the detection of microorganisms with more rigid cell walls, including parasites. We provide a data set that could also be used for benchmarking algorithms to identify and correct for unwanted batch effects. Overall, the findings suggest that all samples of a microbiome study should be stored in the same way. Furthermore, there is a need to mandate more detailed information about sample storage and processing be published together with DNA sequencing data at the International Nucleotide Sequence Database Collaboration (ENA/EBI, NCBI, DDBJ) or other repositories.

Comparison of Fecal Collection Methods on Variation in Gut Metagenomics and Untargeted Metabolomics

Integrative analysis of high-quality metagenomics and metabolomics data from fecal samples provides novel clues for the mechanism underpinning gut microbe-human interactions. However, data regarding the influence of fecal collection methods on both metagenomics and metabolomics are sparse. Six fecal collection methods (the gold standard [GS] [i.e., immediate freezing at −80°C with no solution], 95% ethanol, RNAlater, OMNIgene Gut, fecal occult blood test [FOBT] cards, and Microlution) were used to collect 88 fecal samples from eight healthy volunteers for whole-genome shotgun sequencing (WGSS) and untargeted metabolomic profiling. Metrics assessed included the abundances of predominant phyla and α- and β-diversity at the species, gene, and pathway levels. Intraclass correlation coefficients (ICCs) were calculated for microbes and metabolites to estimate (i) stability (day 4 versus day 0 within each method), (ii) concordance (day 0 for each method versus the GS), and (iii) reliability (day 4 for each method versus the GS). For the top 4 phyla and microbial diversity metrics at the species, gene, and pathway levels, generally high stability and reliability were observed for most methods except for 95% ethanol; similar concordances were seen for different methods. For metabolomics data, 95% ethanol showed the highest stability, concordance, and reliability (median ICCs = 0.71, 0.71, and 0.65, respectively). Taken together, OMNIgene Gut, FOBT cards, RNAlater, and Microlution, but not 95% ethanol, were reliable collection methods for gut metagenomic studies. However, 95% ethanol was the best for preserving fecal metabolite profiles. We recommend using separate collecting methods for gut metagenomic sequencing and fecal metabolomic profiling in large population studies.

IMPORTANCE The choice of fecal collection method is essential for studying gut microbe-human interactions in large-scale population-based research. In this study, we examined the effects of fecal collection methods and storage time at ambient temperature on variations in the gut microbiome community composition; microbial diversity metrics at the species, gene, and pathway levels; antibiotic resistance genes; and metabolome profiling. Our findings suggest using different fecal sample collection methods for different data generation purposes. OMNIgene Gut, FOBT cards, RNAlater, and Microlution, but not 95% ethanol, were reliable collection methods for gut metagenomic studies. However, 95% ethanol was the best for preserving fecal metabolite profiles.

Leveraging Fecal Microbial Markers to Improve the Diagnostic Accuracy of the Fecal Immunochemical Test for Advanced Colorectal Adenoma

INTRODUCTION

Fecal immunochemical tests (FITs) detect colorectal adenoma inefficiently. The gut microbiota participates in colorectal cancer development. We aimed to explore fecal microbial signatures for advanced adenomas and evaluate their diagnostic value and complementary capacity to FIT.

METHODS

Using 16S rRNA sequencing, we studied gut microbiota in feces from 1,546 subjects in a screening setting, including 268 patients with advanced adenomas, 490 patients with nonadvanced adenomas, and 788 healthy subjects. Feature selections were performed using linear discriminant analysis effect size, multivariate association with linear models, and least absolute shrinkage and selection operator. The diagnostic performance of microbial signatures and their auxiliary role to FITs and the added value of the Asia-Pacific Colorectal Screening score were evaluated. We applied 0.632+ bootstrapping to adjust the potential overfitting.

RESULTS

We identified 13 microbial signatures to show the joint diagnostic value for advanced adenoma, with genus Tyzzerella 4 demonstrating the highest adjusted area under the curve (AUC) of 0.545 (95% confidence interval [CI], 0.520-0.610). The 13-bacteria increased the adjusted AUC to 0.607 (95% CI, 0.548-0.660). Compared with individual FIT (adjusted AUC = 0.527; 95% CI, 0.519-0.571), 13-bacteria and FITs collectively reached an adjusted AUC of 0.641 (95% CI, 0.579-0.691). At cutoff values yielding specificities of 90% and 80%, the adjusted sensitivities were 28.4% (95% CI, 19.3-36.8) and 41.1% (95% CI, 29.9-49.4), respectively. The Asia-Pacific Colorectal Screening score further boosted the adjusted AUC to 0.706 (95% CI, 0.648-0.750).

DISCUSSION

In this study using fecal samples from a screening setting, the identified microbial signatures could complement FITs for detecting advanced adenomas. Gut microbiota can act as a promising tool to optimize the current colorectal cancer screening modalities.

Microbiome Analysis of More Than 2,000 NHS Bowel Cancer Screening Programme Samples Shows the Potential to Improve Screening Accuracy

PURPOSE

There is potential for fecal microbiome profiling to improve colorectal cancer screening. This has been demonstrated by research studies, but it has not been quantified at scale using samples collected and processed routinely by a national screening program.

EXPERIMENTAL DESIGN

Between 2016 and 2019, the largest of the NHS Bowel Cancer Screening Programme hubs prospectively collected processed guaiac fecal occult blood test (gFOBT) samples with subsequent colonoscopy outcomes: blood-negative [n = 491 (22%)]; colorectal cancer [n = 430 (19%)]; adenoma [n = 665 (30%)]; colonoscopy-normal [n = 300 (13%)]; nonneoplastic [n = 366 (16%)]. Samples were transported and stored at room temperature. DNA underwent 16S rRNA gene V4 amplicon sequencing. Taxonomic profiling was performed to provide features for classification via random forests (RF).

RESULTS

Samples provided 16S amplicon-based microbial profiles, which confirmed previously described colorectal cancer-microbiome associations. Microbiome-based RF models showed potential as a first-tier screen, distinguishing colorectal cancer or neoplasm (colorectal cancer or adenoma) from blood-negative with AUC 0.86 (0.82-0.89) and AUC 0.78 (0.74-0.82), respectively. Microbiome-based models also showed potential as a second-tier screen, distinguishing from among gFOBT blood-positive samples, colorectal cancer or neoplasm from colonoscopy-normal with AUC 0.79 (0.74-0.83) and AUC 0.73 (0.68-0.77), respectively. Models remained robust when restricted to 15 taxa, and performed similarly during external validation with metagenomic datasets.

CONCLUSIONS

Microbiome features can be assessed using gFOBT samples collected and processed routinely by a national colorectal cancer screening program to improve accuracy as a first- or second-tier screen. The models required as few as 15 taxa, raising the potential of an inexpensive qPCR test. This could reduce the number of colonoscopies in countries that use fecal occult blood test screening.

Long-term storage of feces at -80 °C versus -20 °C is negligible for 16S rRNA amplicon profiling of the equine bacterial microbiome

The development of next-generation sequencing technologies has spurred a surge of research on bacterial microbiome diversity and function. But despite the rapid growth of the field, many uncertainties remain regarding the impact of differing methodologies on downstream results. Sample storage temperature is conventionally thought to be among the most important factors for ensuring reproducibility across marker gene studies, but to date much of the research on this topic has focused on short-term storage in the context of clinical applications. Consequently, it has remained unclear if storage at −80 °C, widely viewed as the gold standard for long-term archival of feces, is truly required for maintaining sample integrity in amplicon-based studies. A better understanding of the impacts of long-term storage conditions is important given the substantial cost and limited availability of ultra-low temperature freezers. To this end, we compared bacterial microbiome profiles inferred from 16S V3–V4 amplicon sequencing for paired fecal samples obtained from a feral horse population from Sable Island, Nova Scotia, Canada, stored at either −80 °C or −20 °C for 4 years. We found that storage temperature did not significantly affect alpha diversity measures, including amplicon sequence variant (ASV) richness and evenness, and abundance of rare sequence variants, nor presence/absence, relative abundances and phylogenetic diversity weighted measures of beta diversity. These results indicate that storage of equine feces at −20 °C for periods ranging from a few months to a few years is equivalent to storage at −80 °C for amplicon-based microbiome studies, adding to accumulating evidence indicating that standard domestic freezers are both economical and effective for microbiome research.

Factors Associated With the Microbiome in Moderate-Late Preterm Babies: A Cohort Study From the DIAMOND Randomized Controlled Trial

The gut microbiota of preterm infants is affected by perinatal factors and, in turn, may impact upon infant health. In this study, we collected fecal samples at Day-10 (D10) and 4-months corrected-age (4M) from 227 moderate–late preterm (MLPT) babies enrolled in a randomized controlled trial of nutritional management. A total of 320 samples underwent 16S amplicon sequencing, and shotgun metagenomic sequencing was performed on 94 samples from the 4M time point. The microbiome of babies whose families lived in lower socioeconomic status (SES) areas exhibited a significantly higher microbial alpha diversity at D10 (Wilcoxon test, p = 0.021), greater abundance of Bifidobacterium (linear model, q = 0.020) at D10 and Megasphaera (q = 0.031) at 4M. Hospital of birth explained 5.2% of the observed variance in 4M samples (PERMANOVA, p = 0.038), with Staphylococcus aureus more abundant in fecal samples from babies born in Middlemore hospital (linear model, q = 0.016). Maternal antibiotic (Wilcoxon test, p = 0.013) and probiotic (p = 0.04) usage within the four-week period before sample collection was associated with a reduction in the alpha diversity of D10 samples. Infant probiotic intake explained 2.1% (PERMANOVA, p = 0.021) of the variance in the D10 microbial profile with increased Lactobacillus (linear model, q = 1.1 × 10⁻¹⁰) levels. At 4M, the microbiome of infants who were breastmilk fed had reduced alpha diversity when compared to non-breastmilk fed infants (Wilcoxon test, p < 0.05). Although causality cannot be inferred within our study, we conclude that in MLPT babies, maternal socioeconomic factors, as well as the perinatal medical environment and nutrition impact on the development of the newborn microbiome.

The colorectal cancer-associated faecal microbiome of developing countries resembles that of developed countries

BACKGROUND

The incidence of colorectal cancer (CRC) is increasing in developing countries, yet limited research on the CRC- associated microbiota has been conducted in these areas, in part due to scarce resources, facilities, and the difficulty of fresh or frozen stool storage/transport. Here, we aimed (1) to establish a broad representation of diverse developing countries (Argentina, Chile, India, and Vietnam); (2) to validate a 'resource-light' sample-collection protocol translatable in these settings using guaiac faecal occult blood test (gFOBT) cards stored and, importantly, shipped internationally at room temperature; (3) to perform initial profiling of the collective CRC-associated microbiome of these developing countries; and (4) to compare this quantitatively with established CRC biomarkers from developed countries.

METHODS

We assessed the effect of international storage and transport at room temperature by replicating gFOBT from five UK volunteers, storing two in the UK, and sending replicates to institutes in the four countries. Next, to determine the effect of prolonged UK storage, DNA extraction replicates for a subset of samples were performed up to 252 days apart. To profile the CRC-associated microbiome of developing countries, gFOBT were collected from 41 treatment-naïve CRC patients and 40 non-CRC controls from across the four institutes, and V4 16S rRNA gene sequencing was performed. Finally, we constructed a random forest (RF) model that was trained and tested against existing datasets from developed countries.

RESULTS

The microbiome was stably assayed when samples were stored/transported at room temperature and after prolonged UK storage. Large-scale microbiome structure was separated by country and continent, with a smaller effect from CRC. Importantly, the RF model performed similarly to models trained using external datasets and identified similar taxa of importance (Parvimonas, Peptostreptococcus, Fusobacterium, Alistipes, and Escherichia).

CONCLUSIONS

This study demonstrates that gFOBT, stored and transported at room temperature, represents a suitable method of faecal sample collection for amplicon-based microbiome biomarkers in developing countries and suggests a CRC-faecal microbiome association that is consistent between developed and developing countries.

Association of Body Mass Index with Fecal Microbial Diversity and Metabolites in the Northern Finland Birth Cohort

BACKGROUND

Obesity is an established risk factor for multiple cancer types. Lower microbial richness has been linked to obesity, but human studies are inconsistent, and associations of early-life body mass index (BMI) with the fecal microbiome and metabolome are unknown.

METHODS

We characterized the fecal microbiome (n = 563) and metabolome (n = 340) in the Northern Finland Birth Cohort 1966 using 16S rRNA gene sequencing and untargeted metabolomics. We estimated associations of adult BMI and BMI history with microbial features and metabolites using linear regression and Spearman correlations (rs ) and computed correlations between bacterial sequence variants and metabolites overall and by BMI category.

RESULTS

Microbial richness, including the number of sequence variants (rs = -0.21, P < 0.0001), decreased with increasing adult BMI but was not independently associated with BMI history. Adult BMI was associated with 56 metabolites but no bacterial genera. Significant correlations were observed between microbes in 5 bacterial phyla, including 18 bacterial genera, and metabolites in 49 of the 62 metabolic pathways evaluated. The genera with the strongest correlations with relative metabolite levels (positively and negatively) were Blautia, Oscillospira, and Ruminococcus in the Firmicutes phylum, but associations varied by adult BMI category.

CONCLUSIONS

BMI is strongly related to fecal metabolite levels, and numerous associations between fecal microbial features and metabolite levels underscore the dynamic role of the gut microbiota in metabolism.

IMPACT

Characterizing the associations between the fecal microbiome, the fecal metabolome, and BMI, both recent and early-life exposures, provides critical background information for future research on cancer prevention and etiology.

The Human Microbiome in Relation to Cancer Risk: A Systematic Review of Epidemiologic Studies

The microbiome has been hypothesized to play a role in cancer development. Because of the diversity of published data, an overview of available epidemiologic evidence linking the microbiome with cancer is now needed. We conducted a systematic review using a tailored search strategy in Medline and EMBASE databases to identify and summarize the current epidemiologic literature on the relationship between the microbiome and different cancer outcomes published until December 2019. We identified 124 eligible articles. The large diversity of parameters used to describe microbial composition made it impossible to harmonize the different studies in a way that would allow meta-analysis, therefore only a qualitative description of results could be performed. Fifty studies reported differences in the gut microbiome between patients with colorectal cancer and various control groups. The most consistent findings were for Fusobacterium, Porphyromonas, and Peptostreptococcus being significantly enriched in fecal and mucosal samples from patients with colorectal cancer. For the oral microbiome, significantly increased and decreased abundance was reported for Fusobacterium and Streptococcus, respectively, in patients with oral cancer compared with controls. Overall, although there was a large amount of evidence for some of these alterations, most require validation in high-quality, preferably prospective, epidemiologic studies.

The Southern Bluefin Tuna Mucosal Microbiome Is Influenced by Husbandry Method, Net Pen Location, and Anti-parasite Treatment

Aquaculture is the fastest growing primary industry worldwide. Marine finfish culture in open ocean net pens, or pontoons, is one of the largest growth areas and is currently the only way to rear high value fish such as bluefin tuna. Ranching involves catching wild juveniles, stocking in floating net pens and fattening for 4 to 8 months. Tuna experience several parasite-induced disease challenges in culture that can be mitigated by application of praziquantel (PZQ) as a therapeutic. In this study, we characterized the microbiome of ranched southern Bluefin Tuna, Thunnus maccoyii, across four anatomic sites (gill, skin, digesta, and anterior kidney) and evaluated environmental and pathological factors that influence microbiome composition, including the impact of PZQ treatment on microbiome stability. Southern bluefin tuna gill, skin, and digesta microbiome communities are unique and potentially influenced by husbandry practices, location of pontoon growout pens, and treatment with the antiparasitic PZQ. There was no significant relationship between the fish mucosal microbiome and incidence or abundance of adult blood fluke in the heart or fluke egg density in the gill. An enhanced understanding of microbiome diversity and function in high-value farmed fish species such as bluefin tuna is needed to optimize fish health and improve aquaculture yield. Comparison of the bluefin tuna microbiome to other fish species, including Seriola lalandi (yellowtail kingfish), a common farmed species from Australia, and Scomber japonicus (Pacific mackerel), a wild caught Scombrid relative of tuna, showed the two Scombrids had more similar microbial communities compared to other families. The finding that mucosal microbial communities are more similar in phylogenetically related fish species exposes an opportunity to develop mackerel as a model for tuna microbiome and parasite research.

The microbiome: an emerging key player in aging and longevity

Revolutionary advancements of high-throughput sequencing and metagenomic tools have provided new insights to microbiome function, including a bidirectional relationship between the microbiome and host aging. The intestinal tract is the largest surface in the human body that directly interacts with foreign antigens - it is covered with extremely complex and diverse community of microorganisms, known as the gut microbiome. In a healthy gut, microbial communities maintain a homeostatic metabolism and reside within the host in a state of immune tolerance. Abnormal shifts in the gut microbiome, however, have been implicated in the pathogenesis of age-related chronic diseases, including obesity, cardiovascular diseases and neurodegenerative diseases. The gut microbiome is emerging as a key factor in the aging process. In this review, we describe studies of humans and model organisms that suggest a direct causal role of the gut microbiome on host aging. Additionally, we also discuss sex-dimorphism in the gut microbiome and its possible roles in age-related sex-dimorphic phenotypes. We also provide an overview of widely used microbiome analysis methods and tools which could be used to explore the impact of microbiome remodeling on aging.

Current Sampling Methods for Gut Microbiota: A Call for More Precise Devices

The development of next-generation sequencing technology has enabled researchers to explore and understand the gut microbiome from a broader and deeper perspective. However, the results of different studies on gut microbiota are highly variable even in the same disease, which makes it difficult to guide clinical diagnosis and treatment. The ideal sampling method should be non-invasive, involve little cross-contamination or bowel preparation, and collect gut microbiota at different sites. Currently, sequencing technologies are usually based on samples collected from feces, mucosal biopsy, intestinal fluid, etc. However, different parts of the gastrointestinal tract possess various physiological characteristics that are essential for particular species of living microbiota. Moreover, current sampling methods are somewhat defective. For example, fecal samples are just a proxy for intestinal microbiota, while biopsies are invasive for patients and not suitable for healthy controls. In this review, we summarize the current sampling methods and their advantages and shortcomings. New sampling technologies, such as the Brisbane Aseptic Biopsy Device and the intelligent capsule, are also mentioned to inspire the development of future precise description methods of the gut microbiome.

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.

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.

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.

Benchmarking urine storage and collection conditions for evaluating the female urinary microbiome

Standardized conditions for collection, preservation and storage of urine for microbiome research have not been established. We aimed to identify the effects of the use of preservative AssayAssure® (AA), and the effects of storage time and temperatures on reproducibility of urine microbiome results. We sequenced the V3-4 segment of the 16S rRNA gene to characterize the bacterial community in the urine of a cohort of women. Each woman provided a single voided urine sample, which was divided into aliquots and stored with and without AA, at three different temperatures (room temperature [RT], 4 °C, or -20 °C), and for various time periods up to 4 days. There were significant microbiome differences in urine specimens stored with and without AA at all temperatures, but the most significant differences were observed in alpha diversity (estimated number of taxa) at RT. Specimens preserved at 4 °C and -20 °C for up to 4 days with or without AA had no significant alpha diversity differences. However, significant alpha diversity differences were observed in samples stored without AA at RT. Generally, there was greater microbiome preservation with AA than without AA at all time points and temperatures, although not all results were statistically significant. Addition of AA preservative, shorter storage times, and colder temperatures are most favorable for urinary microbiome reproducibility.

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.

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.

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.

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.

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.

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.