Intricacies of assessing the human microbiome in epidemiologic studies

Sample Size Estimations Based on Human Microbiome Temporal Stability Over 6 Months: A Shallow Shotgun Metagenome Sequencing Analysis

BACKGROUND

Biological factors affect the human microbiome, highlighting the need for reasonably estimating sample sizes in future population studies.

METHODS

We assessed the temporal stability of fecal microbiome diversity, species composition, and genes and functional pathways through shallow shotgun metagenome sequencing. Using intraclass correlation coefficients (ICC), we measured biological variability over 6 months. We estimated case numbers for 1:1 or 1:3 matched case-control studies, considering significance levels of 0.05 and 0.001 with 80% power, based on the collected fecal specimens per participant.

RESULTS

The fecal microbiome's temporal stability over 6 months varied (ICC < 0.6) for most alpha and beta diversity metrics. Heterogeneity was seen in species, genes, and pathways stability (ICC, 0.0-0.9). Detecting an OR of 1.5 per SD required 1,000 to 5,000 cases (0.05 significance for alpha and beta; 0.001 for species, genes, and pathways) with equal cases and controls. Low-prevalence species needed 15,102 cases, and high-prevalence species required 3,527. Similar needs applied to genes and pathways. In a 1:3 matched case-control study with one fecal specimen, 10,068 cases were needed for low-prevalence species and 2,351 for high-prevalence species. For ORs of 1.5 with multiple specimens, cases needed for low-prevalence species were 15,102 (one specimen), 8,267 (two specimens), and 5,989 (three specimens).

CONCLUSIONS

Detecting disease associations requires a large number of cases. Repeating prediagnostic samples and matching cases to more controls could decrease the needed number of cases for such detections.

IMPACT

Our results will help future epidemiologic study designs and implement well-powered microbiome studies.

The gut microbiome and dietary metabolites in the treatment of renal cell carcinoma

The gut microbiome is interlinked with renal cell carcinoma (RCC) and its response to systemic treatment. Mounting data suggests that certain elements of the gut microbiome may correlate with improved outcomes. New generation sequencing techniques and advanced bioinformatic data curation are accelerating the investigation of specific markers and metabolites that could predict treatment response. A variety of new therapeutic strategies, such as fecal microbiota transplantation, probiotic supplements, and dietary interventions, are currently being developed to modify the gut microbiome and improve anticancer therapies in patients with RCC. This review discusses the preliminary evidence indicating the role of the microbiome in cancer treatment, the techniques and tools necessary for its proper study and some of the current forms with which the microbiome can be modulated to improve patient outcomes.

Examining the healthy human microbiome concept

Human microbiomes are essential to health throughout the lifespan and are increasingly recognized and studied for their roles in metabolic, immunological and neurological processes. Although the full complexity of these microbial communities is not fully understood, their clinical and industrial exploitation is well advanced and expanding, needing greater oversight guided by a consensus from the research community. One of the most controversial issues in microbiome research is the definition of a 'healthy' human microbiome. This concept is complicated by the microbial variability over different spatial and temporal scales along with the challenge of applying a unified definition to the spectrum of healthy microbiome configurations. In this Perspective, we examine the progress made and the key gaps that remain to be addressed to fully harness the benefits of the human microbiome. We propose a road map to expand our knowledge of the microbiome-health relationship, incorporating epidemiological approaches informed by the unique ecological characteristics of these communities.

The salivary microbiome as a diagnostic biomarker of periodontitis: a 16S multi-batch study before and after the removal of batch effects

Introduction

Microbiome-based clinical applications that improve diagnosis related to oral health are of great interest to precision dentistry. Predictive studies on the salivary microbiome are scarce and of low methodological quality (low sample sizes, lack of biological heterogeneity, and absence of a validation process). None of them evaluates the impact of confounding factors as batch effects (BEs). This is the first 16S multi-batch study to analyze the salivary microbiome at the amplicon sequence variant (ASV) level in terms of differential abundance and machine learning models. This is done in periodontally healthy and periodontitis patients before and after removing BEs.

Methods

Saliva was collected from 124 patients (50 healthy, 74 periodontitis) in our setting. Sequencing of the V3-V4 16S rRNA gene region was performed in Illumina MiSeq. In parallel, searches were conducted on four databases to identify previous Illumina V3-V4 sequencing studies on the salivary microbiome. Investigations that met predefined criteria were included in the analysis, and the own and external sequences were processed using the same bioinformatics protocol. The statistical analysis was performed in the R-Bioconductor environment.

Results

The elimination of BEs reduced the number of ASVs with differential abundance between the groups by approximately one-third (Before=265; After=190). Before removing BEs, the model constructed using all study samples (796) comprised 16 ASVs (0.16%) and had an area under the curve (AUC) of 0.944, sensitivity of 90.73%, and specificity of 87.16%. The model built using two-thirds of the specimens (training=531) comprised 35 ASVs (0.36%) and had an AUC of 0.955, sensitivity of 86.54%, and specificity of 90.06% after being validated in the remaining one-third (test=265). After removing BEs, the models required more ASVs (all samples=200-2.03%; training=100-1.01%) to obtain slightly lower AUC (all=0.935; test=0.947), lower sensitivity (all=81.79%; test=78.85%), and similar specificity (all=91.51%; test=90.68%).

Conclusions

The removal of BEs controls false positive ASVs in the differential abundance analysis. However, their elimination implies a significantly larger number of predictor taxa to achieve optimal performance, creating less robust classifiers. As all the provided models can accurately discriminate health from periodontitis, implying good/excellent sensitivities/specificities, the salivary microbiome demonstrates potential clinical applicability as a precision diagnostic tool for periodontitis.

Relationships between the vaginal microbiota and genitourinary syndrome of menopause symptoms in postmenopausal women: the Study of Women's Health Across the Nation

OBJECTIVE

To describe vaginal microbiota classified by community state types (CST) in a diverse cohort of postmenopausal women and evaluate relationships among genitourinary syndrome of menopause (GSM) symptoms (vaginal dryness, vulvovaginal irritation, sexual pain, dysuria, urinary urgency), CSTs, estrogen, vaginal maturation index (VMI), and vaginal pH.

METHODS

In the Study of Women's Health Across the Nation, 1,320 women aged 60.4 to 72.5 years self-collected (2015-2017) vaginal samples analyzed for microbiota composition and structure (CSTs) using 16S rRNA gene amplicon sequencing, VMI, and pH. GSM symptoms were collected with self-administered questionnaires; interviewers elicited estrogen use and measured body mass index. Serum E2 and E1 were measured using high-performance liquid chromatography. We analyzed data using Pearson χ2 tests, analysis of variance, Kruskal-Wallis tests, and binomial logistic regression.

RESULTS

The most frequently occurring CST was low Lactobacillus species IV-C (49.8%); 36.4% of women had CSTs dominated by Lactobacillus species. More than half of the women with vaginal atrophy biomarkers (VMI <50 and pH >5) had CST IV-C0, whereas women using estrogen or with higher E1 and E2 levels had a higher prevalence of Lactobacillus crispatus -dominated CST I ( P values < 0.001). Sexual pain was associated with atrophy biomarkers and independently associated with Streptococcus species-dominated CST IV-C1 (odds ratio, 2.26; 95% confidence intervals, 1.20-4.23). For all other GSM symptoms, we found no consistent associations with E1 or E2 levels, atrophy biomarkers, or any CST.

CONCLUSIONS

Although close relationships exist among estrogen, CSTs, VMI, and pH, sexual pain was the only GSM symptom associated with the structure of vaginal microbiota and atrophy biomarkers.

Critical review of 16S rRNA gene sequencing workflow in microbiome studies: From primer selection to advanced data analysis

The multi-batch reanalysis approach of jointly reevaluating gene/genome sequences from different works has gained particular relevance in the literature in recent years. The large amount of 16S ribosomal ribonucleic acid (rRNA) gene sequence data stored in public repositories and information in taxonomic databases of the same gene far exceeds that related to complete genomes. This review is intended to guide researchers new to studying microbiota, particularly the oral microbiota, using 16S rRNA gene sequencing and those who want to expand and update their knowledge to optimise their decision-making and improve their research results. First, we describe the advantages and disadvantages of using the 16S rRNA gene as a phylogenetic marker and the latest findings on the impact of primer pair selection on diversity and taxonomic assignment outcomes in oral microbiome studies. Strategies for primer selection based on these results are introduced. Second, we identified the key factors to consider in selecting the sequencing technology and platform. The process and particularities of the main steps for processing 16S rRNA gene-derived data are described in detail to enable researchers to choose the most appropriate bioinformatics pipeline and analysis methods based on the available evidence. We then produce an overview of the different types of advanced analyses, both the most widely used in the literature and the most recent approaches. Several indices, metrics and software for studying microbial communities are included, highlighting their advantages and disadvantages. Considering the principles of clinical metagenomics, we conclude that future research should focus on rigorous analytical approaches, such as developing predictive models to identify microbiome-based biomarkers to classify health and disease states. Finally, we address the batch effect concept and the microbiome-specific methods for accounting for or correcting them.

A Narrative Review Discussing the Obstetric Repercussions Due to Alterations of Personalized Bacterial Sites Developed within the Vagina, Cervix, and Endometrium

BACKGROUND

The reproductive tract microbiota that evolved as an integrative component has been studied intensively in the last decade. As a result, novel research, clinical opportunities, and perspectives have been derived following the close investigation of this microecological environment. This has paved the way for an update to and improvement of the management strategies and therapeutic approaches. However, obscurities, contradictions, and controversies arise regarding the ascension route from the vagina to the endometrium via the cervix, with finality in adverse obstetric outcomes.

METHODS

Starting from these considerations, we aimed to gather all existing data and information from four major academic databases (PubMed, ISI Web of Knowledge, Scopus, and ScienceDirect) published in the last 13 years (2010-2023) using a controlled vocabulary and dedicated terminology to enhance the coverage, identification, and sorting of potentially eligible studies.

RESULTS

Despite the high number of returned entries (n = 804), only a slight percentage (2.73%) of all manuscripts were deemed eligible following two rounds of evaluation. Cumulatively, a low level of Lactobacillus spp. and of other core microbiota members is mandatory, with a possible eubiosis-to-dysbiosis transition leading to an impairment of metabolic and endocrine network homeostasis. This transposes into a change in the pro-inflammatory landscape and activation of signaling pathways due to activity exerted by the bacterial lipopolysaccharides (LPSs)/endotoxins that further reflect a high risk of miscarriage in various stages. While the presence of some pathogenic entities may be suggestive of an adverse obstetric predisposition, there are still pros and cons of the role of specific strains, as only the vagina and cervix have been targeted as opposed to the endometrium, which recently started to be viewed as the key player in the vagina-cervix-endometrium route. Consequently, based on an individual's profile, diet, and regime, antibiotics and probiotics might be practical or not.

CONCLUSIONS

Resident bacteria have a dual facet and are beneficial for women's health, but, at the same time, relaying on the abundance, richness, and evenness that are definitory indexes standing as intermediaries of a miscarriage.

In silico evaluation and selection of the best 16S rRNA gene primers for use in next-generation sequencing to detect oral bacteria and archaea

BACKGROUND

Sequencing has been widely used to study the composition of the oral microbiome present in various health conditions. The extent of the coverage of the 16S rRNA gene primers employed for this purpose has not, however, been evaluated in silico using oral-specific databases. This paper analyses these primers using two databases containing 16S rRNA sequences from bacteria and archaea found in the human mouth and describes some of the best primers for each domain.

RESULTS

A total of 369 distinct individual primers were identified from sequencing studies of the oral microbiome and other ecosystems. These were evaluated against a database reported in the literature of 16S rRNA sequences obtained from oral bacteria, which was modified by our group, and a self-created oral archaea database. Both databases contained the genomic variants detected for each included species. Primers were evaluated at the variant and species levels, and those with a species coverage (SC) ≥75.00% were selected for the pair analyses. All possible combinations of the forward and reverse primers were identified, with the resulting 4638 primer pairs also evaluated using the two databases. The best bacteria-specific pairs targeted the 3-4, 4-7, and 3-7 16S rRNA gene regions, with SC levels of 98.83-97.14%; meanwhile, the optimum archaea-specific primer pairs amplified regions 5-6, 3-6, and 3-6, with SC estimates of 95.88%. Finally, the best pairs for detecting both domains targeted regions 4-5, 3-5, and 5-9, and produced SC values of 95.71-94.54% and 99.48-96.91% for bacteria and archaea, respectively.

CONCLUSIONS

Given the three amplicon length categories (100-300, 301-600, and >600 base pairs), the primer pairs with the best coverage values for detecting oral bacteria were as follows: KP_F048-OP_R043 (region 3-4; primer pair position for Escherichia coli J01859.1: 342-529), KP_F051-OP_R030 (4-7; 514-1079), and KP_F048-OP_R030 (3-7; 342-1079). For detecting oral archaea, these were as follows: OP_F066-KP_R013 (5-6; 784-undefined), KP_F020-KP_R013 (3-6; 518-undefined), and OP_F114-KP_R013 (3-6; 340-undefined). Lastly, for detecting both domains jointly they were KP_F020-KP_R032 (4-5; 518-801), OP_F114-KP_R031 (3-5; 340-801), and OP_F066-OP_R121 (5-9; 784-1405). The primer pairs with the best coverage identified herein are not among those described most widely in the oral microbiome literature. Video Abstract.

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.

Role of microbiota and microbiota-derived short-chain fatty acids in PDAC

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive lethal diseases among other cancer types. Gut microbiome and its metabolic regulation play a crucial role in PDAC. Metabolic regulation in the gut is a complex process that involves microbiome and microbiome-derived short-chain fatty acids (SCFAs). SCFAs regulate inflammation, as well as lipid and glucose metabolism, through different pathways. This review aims to summarize recent developments in PDAC in the context of gut and oral microbiota and their associations with short-chain fatty acid (SCFA). In addition to this, we discuss possible therapeutic applications using microbiota in PDAC.

Vaginal Atopobium is Associated with Spontaneous Abortion in the First Trimester: a Prospective Cohort Study in China

Spontaneous abortion (SA) has received more and more attention in light of its increasing incidence. However, the causes and pathogenesis of SA remain largely unknown, especially for those without any pathological features. In this study, we characterized the vaginal microbiota diversity and composition of pregnant women in their first trimester and evaluated the association between the vaginal microbiota and SA before 12 weeks of gestation. Participants' bacterial profiles were analyzed by 16S rRNA gene sequencing in the V3-V4 regions at 5-8 weeks of gestation. A total of 48 patients with SA at 12 weeks of gestation were included as the study group, while 116 women with normal pregnancies (NPs) were included as a control group. The results indicated that the richness of the vaginal microbiome in SA patients was higher (Chao1, P < 0.05) and different in composition relative to that of women with NPs (unweighted UniFrac, R = 0.15, P < 0.01; binary Jaccard, R = 0.15, P < 0.01). Furthermore, the genus Apotobium was significantly enriched in SA patients. An extreme gradient-boosting (XGBoost) analysis was able to classify Atopobium-induced SA more reliably (area under the receiver operating characteristic curve, 0.69; threshold, 0.01%). Moreover, after adjusting for potential confounders, the results showed a robust association between Apotobium and SA (as a categorical variable [<0.01%]; adjusted odds ratio, 2.9; 95% confidence interval, 1.3 to 6.5; P = 0.01). In conclusion, higher vaginal Apotobium levels were associated with SA in the first trimester. IMPORTANCE Spontaneous abortion (SA) is the most common adverse pregnancy outcome in the first trimester. The causal drivers of SA have become a substantial challenge to reveal and overcome. We hypothesize that vaginal microbial dysbiosis is associated with SA, as it was related to several female reproductive disorders in previous studies. In our study, we characterized the vaginal microbiota of patients with SA at 12 weeks of gestation as the study group, and women with normal pregnancies were enrolled as a control group. Generally, significant differences were discovered in the vaginal microbiota between the two groups. Our study also revealed that Apotobium may play an important role in the pathogenesis of SA. To our knowledge, this study is the first detailed elaboration of the vaginal microbiota composition and vaginal Apotobium in association with SA. We believe that our findings will inspire more researchers to consider dynamic changes in the vaginal microbiota as critical features for further studies of nosogenesis not only for SA but also other reproductive diseases.

Association Between Vaginal Gardnerella and Tubal Pregnancy in Women With Symptomatic Early Pregnancies in China: A Nested Case-Control Study

The early diagnosis and treatment of ectopic pregnancy (EP) remains a major challenge. Despite a known link between vaginal microbiota and female reproductive health, few studies have focused on the association between vaginal microbiota and pregnancy location. This nested case-control study aimed to characterize the vaginal microbiota in tubal pregnancy (TP) among symptomatic women in early pregnancy. Women with symptomatic early pregnancy of unknown location (PUL) were included in this study. 16S rDNA gene sequencing was performed to assess vaginal microbial diversity and relative abundance. Machine learning and multivariate logistic regression were also used to evaluate the association between Gardnerella and TP. The results indicate that the vaginal microbiome in TP was more diverse (Shannon, p < 0.05) and was different in composition to that of women with intrauterine pregnancy (IUP) (weighted Unifrac, R = 0.08, p = 0.01). The genus Gardnerella was significantly enriched in TP. The XGBoost analysis was able to classify Gardnerella-induced TP more reliably (AUC = 0.621). Moreover, after adjusting potential confounders, our results indicate a robust association between Gardnerella and TP (as a continuous variable, adjusted OR: 12.0, 95% CI: 2.1–67.4, p < 0.01; as a categorical variable (≥0.85%), and adjusted OR: 4.2, 95% CI: 2.0–8.8, p < 0.01). In conclusion, we found that higher virginal Gardnerella levels were associated with TP in women with symptomatic early pregnancy.

Non-Lactobacillus-Dominated Vaginal Microbiota Is Associated With a Tubal Pregnancy in Symptomatic Chinese Women in the Early Stage of Pregnancy: A Nested Case-Control Study

The features of the vaginal microbiota (VM) community can reflect health status, and they could become new biomarkers for disease diagnosis. During pregnancy, domination of bacteria of the genus Lactobacillus in the VM community is regarded as a keystone because they stabilize the VM by producing antimicrobial compounds and competing adhesion. An altered VM composition provides a marker for adverse pregnancy outcomes. This nested case–control study aimed to characterize the VM in women with a tubal pregnancy (TP) presenting with pain and/or uterine bleeding in early pregnancy. Chinese women with a symptomatic early pregnancy of unknown location were the study cohort. 16S rDNA gene-sequencing of V3–V4 variable regions was done to assess the diversity, structures, taxonomic biomarkers, and classification of the VM community. The primary outcome was the location of the early pregnancy. The VM community in women with a TP showed higher diversity (PD-whole-tree, median: 8.26 vs. 7.08, P = 0.047; Shannon Diversity Index, median: 1.43 vs 0.99, P = 0.03) and showed different structures to those in women with an intrauterine pregnancy (IUP) (R = 0.23, P < 0.01). Bacteria of the genus Lactobacillus were significantly enriched in the IUP group, whereas bacteria of the genera Gardnerella and Prevotella were significantly enriched in the TP group. Lactobacillus abundance could be used to classify the pregnancy location (AUC = 0.81). Non-Lactobacillus-dominated microbiota (≤ 0.85% Lactobacillus) was significantly associated with a TP (adjusted odds ratio: 4.42, 95% confidence interval: 1.33 to 14.71, P = 0.02). In conclusion, among women with a symptomatic early pregnancy, a higher diversity and lower abundance of Lactobacillus in the VM is associated with a TP.

Relationship between dental and periodontal health status and the salivary microbiome: bacterial diversity, co-occurrence networks and predictive models

The present study used 16S rRNA gene amplicon sequencing to assess the impact on salivary microbiome of different grades of dental and periodontal disease and the combination of both (hereinafter referred to as oral disease), in terms of bacterial diversity, co-occurrence network patterns and predictive models. Our scale of overall oral health was used to produce a convenience sample of 81 patients from 270 who were initially recruited. Saliva samples were collected from each participant. Sequencing was performed in Illumina MiSeq with 2 × 300 bp reads, while the raw reads were processed according to the Mothur pipeline. The statistical analysis of the 16S rDNA sequencing data at the species level was conducted using the phyloseq, DESeq2, Microbiome, SpiecEasi, igraph, MixOmics packages. The simultaneous presence of dental and periodontal pathology has a potentiating effect on the richness and diversity of the salivary microbiota. The structure of the bacterial community in oral health differs from that present in dental, periodontal or oral disease, especially in high grades. Supragingival dental parameters influence the microbiota’s abundance more than subgingival periodontal parameters, with the former making a greater contribution to the impact that oral health has on the salivary microbiome. The possible keystone OTUs are different in the oral health and disease, and even these vary between dental and periodontal disease: half of them belongs to the core microbiome and are independent of the abundance parameters. The salivary microbiome, involving a considerable number of OTUs, shows an excellent discriminatory potential for distinguishing different grades of dental, periodontal or oral disease; considering the number of predictive OTUs, the best model is that which predicts the combined dental and periodontal status.

Increasing Reproducibility in Oral Microbiome Research

Evidence on the role of the oral microbiome in health and disease is changing the way we understand, diagnose, and treat ailments. Numerous studies on diseases affecting the oral cavity have revealed a large amount of data that is invaluable for the advancements in diagnosing and treating these diseases. However, the clinical translation of most of these exploratory data is stalled by variable methodology between studies and non-uniform reporting of the data.Understanding the key areas that are gateways to bias in microbiome studies is imperative to overcome this challenge faced by oral microbiome research. Bias can be multifactorial and may be introduced in a microbiome research study during the formulation of the study design, sample collection and storage, or the sample processing protocols before sequencing. This chapter summarizes the recommendations from literature to eliminate bias in the microbiome research studies and to ensure the reproducibility of the microbiome research data.

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.

Poultry processing and the application of microbiome mapping

Chicken is globally one of the most popular food animals. However, it is also one of the major reservoirs for foodborne pathogens, annually resulting in continued morbidity and mortality incidences worldwide. In an effort to reduce the threat of foodborne disease, the poultry industry has implemented a multifaceted antimicrobial program that incorporates not only chemical compounds, but also extensive amounts of water application and pathogen monitoring. Unfortunately, the pathogen detection methods currently used by the poultry industry lack speed, relying on microbiological plate methods and molecular detection systems that take time and lack precision. In many cases, the time to data acquisition can take 12 to 24 h. This is problematic if shorter-term answers are required which is becoming more likely as the public demand for chicken meat is only increasing, leading to new pressures to increase line speed. Therefore, new innovations in detection methods must occur to mitigate the risk of foodborne pathogens that could result from faster slaughter and processing speeds. Future technology will have 2 tracks: rapid methods that are meant to detect pathogens and indicator organisms within a few hours, and long-term methods that use microbiome mapping to evaluate sanitation and antimicrobial efficacy. Together, these methods will provide rapid, comprehensive data capable of being applied in both risk-assessment algorithms and used by management to safeguard the public.

Vasoactive Intestinal Peptide Deficiency Is Associated With Altered Gut Microbiota Communities in Male and Female C57BL/6 Mice

Vasoactive intestinal peptide (VIP) is crucial for gastrointestinal tract (GIT) health. VIP sustains GIT homeostasis through maintenance of the intestinal epithelial barrier and acts as a potent anti-inflammatory mediator that contributes to gut bacterial tolerance. Based on these biological functions by VIP, we hypothesized that its deficiency would alter gut microbial ecology. To this end, fecal samples from male and female VIP+/+, VIP+/-, and VIP-/- littermates (n = 47) were collected and 16S rRNA sequencing was conducted. Our data revealed significant changes in bacterial composition, biodiversity, and weight loss from VIP-/- mice compared to VIP+/+ and VIP+/- littermates, irrespective of sex. The gut bacteria compositional changes observed in VIP-/- mice was consistent with gut microbial structure changes reported for certain inflammatory and autoimmune disorders. Moreover, predicted functional changes by PICRUSt software suggested an energy surplus within the altered microbiota from VIP-/- mice. These data support that VIP plays an important role in maintaining microbiota balance, biodiversity, and GIT function, and its genetic removal results in significant gut microbiota restructuring and weight loss.

Sick Individuals and Sick (Microbial) Populations: Challenges in Epidemiology and the Microbiome

The human microbiome represents a new frontier in understanding the biology of human health. While epidemiology in this area is still in its infancy, its scope will likely expand dramatically over the coming years. To rise to the challenge, we argue that epidemiology should capitalize on its population perspective as a critical complement to molecular microbiome research, allowing for the illumination of contextual mechanisms that may vary more across populations rather than among individuals. We first briefly review current research on social context and the gut microbiome, focusing specifically on socioeconomic status (SES) and race/ethnicity. Next, we reflect on the current state of microbiome epidemiology through the lens of one specific area, the association of the gut microbiome and metabolic disorders. We identify key methodological shortcomings of current epidemiological research in this area, including extensive selection bias, the use of noncompositionally robust measures, and a lack of attention to social factors as confounders or effect modifiers.

Is the Oral Microbiome Associated with Blood Pressure in Older Women?

INTRODUCTION

A possible role of the oral microbiome, specifically oral nitrate reducing flora, in blood pressure (BP) homeostasis, if proven etiologic in nature, could lead to novel mechanism-based therapy to improve hypertension prevention and control.

AIM

This cross-sectional study characterized and compared the oral microbiome between four study groups based on BP status among 446 postmenopausal women aged 53-82 years.

METHODS

Three study groups were not taking hypertension medication and were separated based on BP, as follows: normal BP (systolic < 120 and diastolic < 80; N = 179), elevated BP/Stage I hypertension (systolic 120-139 or diastolic 80-90; N = 106), Stage II hypertension (systolic > 140 or diastolic > 90; N = 42). The forth group consisted of anyone taking hypertension medications, regardless of BP (N = 119). Subgingival microbiome composition was determined using 16S rRNA sequencing with the Illumina MiSeq platform. Kruskal-Wallis tests were used to compare species-level relative abundance of bacterial operational taxonomic units across the four groups.

RESULTS

Sixty-five bacterial species demonstrated significant differences in relative abundance in women with elevated BP or using hypertension medication as compared to those with normal BP. After correction for multiple testing, two species, Prevotella oral (species 317) and Streptococcus oralis, remained significant and were lower in abundance among women taking antihypertension medications compared to those with normal BP (corrected P < 0.05).

CONCLUSIONS

These data provide novel description of oral subgingival bacteria grouped according to BP status. Additional larger studies including functional analysis and prospective designs will help further assess the potential role of the oral microbiome in BP regulation and hypertension.

A Review of Prebiotics Against Salmonella in Poultry: Current and Future Potential for Microbiome Research Applications

Prebiotics are typically fermentable feed additives that can directly or indirectly support a healthy intestinal microbiota. Prebiotics have gained increasing attention in the poultry industry as wariness toward antibiotic use has grown in the face of foodborne pathogen drug resistance. Their potential as feed additives to improve growth, promote beneficial gastrointestinal microbiota, and reduce human-associated pathogens, has been well documented. However, their mechanisms remain relatively unknown. Prebiotics increasing short chain fatty acid (SCFA) production in the cecum have long since been considered a potential source for pathogen reduction. It has been previously concluded that prebiotics can improve the safety of poultry products by promoting the overall health and well-being of the bird as well as provide for an intestinal environment that is unfavorable for foodborne pathogens such as Salmonella. To better understand the precise benefit conferred by several prebiotics, "omic" technologies have been suggested and utilized. The data acquired from emerging technologies of microbiomics and metabolomics may be able to generate a more comprehensive detailed understanding of the microbiota and metabolome in the poultry gastrointestinal tract. This understanding, in turn, may allow for improved administration and optimization of prebiotics to prevent foodborne illness as well as elucidate unknown mechanisms of prebiotic actions. This review explores the use of prebiotics in poultry, their impact on gut Salmonella populations, and how utilization of next-generation technologies can elucidate the underlying mechanisms of prebiotics as feed additives.

Akkermansia muciniphila as a Model Case for the Development of an Improved Quantitative RPA Microbiome Assay

Changes in the population levels of specific bacterial species within the gut microbiome have been linked to a variety of illnesses. Most assays that determine the relative abundance of specific taxa are based on amplification and sequencing of stable phylogenetic gene regions. Such lab-based analysis requires pre-analytical sample preservation and storage that have been shown to introduce biases in the characterization of microbial profiles. Recombinase polymerase amplification (RPA) is an isothermal nucleic acid amplification method that employs commercially available, easy-to-use freeze-dried enzyme pellets that can be used to analyze specimens rapidly in the field or clinic, using a portable fluorometer. Immediate analysis of diverse bacterial communities can lead to a more accurate quantification of relative bacterial abundance. In this study, we discovered that universal bacterial 16S ribosomal DNA primers give false-positive signals in RPA analysis because manufacturing host Escherichia coli DNA is present in the RPA reagents. The manufacturer of RPA reagents advises against developing an RPA assay that detects the presence of E. coli due to the presence of contaminating E. coli DNA in the reaction buffer (www.twistdx.co.uk/). We, therefore, explored four strategies to deplete or fragment extraneous DNA in RPA reagents while preserving enzyme activity: metal-chelate affinity chromatography, sonication, DNA cleavage using methylation-dependent restriction endonucleases, and DNA depletion using anti-DNA antibodies. Removing DNA with anti-DNA antibodies enabled the development of a quantitative RPA microbiome assay capable of determining the relative abundance of the physiologically-important bacterium Akkermansia muciniphila in human feces.

Selection of validated hypervariable regions is crucial in 16S-based microbiota studies of the female genital tract

Next-generation sequencing-based methods are extensively applied in studies of the human microbiota using partial 16 S rRNA gene amplicons. However, they carry drawbacks that are critical to consider when interpreting results, including differences in outcome based on the hypervariable region(s) used. Here, we show that primers spanning the V3/V4 region identify a greater number of taxa in the vaginal microbiota than those spanning the V1/V2 region. In particular, taxa such as Gardnerella vaginalis, Bifidobacterium bifidum and Chlamydia trachomatis, all species that influence vaginal health and disease, are not represented in V1/V2-based community profiles. Accordingly, missing or underestimating the frequency of these species overestimates the abundance of other taxa and fails to correctly assess the bacterial diversity in the urogenital tract. We elaborate that covering these taxa using the V3/V4 region leads to profound changes in the assignment of community state types. Altogether, we show that the choice of primers used for studying the vaginal microbiota has deep implications on the biological evaluation of the results.

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

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

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

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

Microbiota changes impact on sexually transmitted infections and the development of pelvic inflammatory disease

The integrity of the human urogenital microbiome is crucial for women's health and well-being. An imbalance of the urogenital microbiota increases the risk for sexually transmitted infections. In this review, we discuss the microbiota composition of the female urogenital tract and its role in protecting from sexually transmitted infections and the emergence of pelvic inflammatory disease.

Microbiome Datasets Are Compositional: And This Is Not Optional

Datasets collected by high-throughput sequencing (HTS) of 16S rRNA gene amplimers, metagenomes or metatranscriptomes are commonplace and being used to study human disease states, ecological differences between sites, and the built environment. There is increasing awareness that microbiome datasets generated by HTS are compositional because they have an arbitrary total imposed by the instrument. However, many investigators are either unaware of this or assume specific properties of the compositional data. The purpose of this review is to alert investigators to the dangers inherent in ignoring the compositional nature of the data, and point out that HTS datasets derived from microbiome studies can and should be treated as compositions at all stages of analysis. We briefly introduce compositional data, illustrate the pathologies that occur when compositional data are analyzed inappropriately, and finally give guidance and point to resources and examples for the analysis of microbiome datasets using compositional data analysis.

Assessment of variation in microbial community amplicon sequencing by the Microbiome Quality Control (MBQC) project consortium

In order for human microbiome studies to translate into actionable outcomes for health, meta-analysis of reproducible data from population-scale cohorts is needed. Achieving sufficient reproducibility in microbiome research has proven challenging. We report a baseline investigation of variability in taxonomic profiling for the Microbiome Quality Control (MBQC) project baseline study (MBQC-base). Blinded specimen sets from human stool, chemostats, and artificial microbial communities were sequenced by 15 laboratories and analyzed using nine bioinformatics protocols. Variability depended most on biospecimen type and origin, followed by DNA extraction, sample handling environment, and bioinformatics. Analysis of artificial community specimens revealed differences in extraction efficiency and bioinformatic classification. These results may guide researchers in experimental design choices for gut microbiome studies.

Risk of heterosexual HIV transmission attributable to sexually transmitted infections and non-specific genital inflammation in Zambian discordant couples, 1994-2012

Background

Studies have demonstrated the role of ulcerative and non-ulcerative sexually transmitted infections (STI) in HIV transmission/acquisition risk; less is understood about the role of non-specific inflammatory genital abnormalities.

Methods

HIV-discordant heterosexual Zambian couples were enrolled into longitudinal follow-up (1994-2012). Multivariable models estimated the effect of genital ulcers and inflammation in both partners on time-to-HIV transmission within the couple. Population-attributable fractions (PAFs) were calculated.

Results

A total of 207 linked infections in women occurred over 2756 couple-years (7.5/100 CY) and 171 in men over 3216 CY (5.3/100 CY). Incident HIV among women was associated with a woman's non-STI genital inflammation (adjusted hazard ratio (aHR) = 1.55; PAF = 8%), bilateral inguinal adenopathy (BIA; aHR = 2.33; PAF = 8%), genital ulceration (aHR = 2.08; PAF = 7%) and the man's STI genital inflammation (aHR = 3.33; PAF = 5%), BIA (aHR = 3.35; PAF = 33%) and genital ulceration (aHR = 1.49; PAF = 9%). Infection among men was associated with a man's BIA (aHR = 4.11; PAF = 22%) and genital ulceration (aHR = 3.44; PAF = 15%) as well as with the woman's non-STI genital inflammation (aHR = 1.92; PAF = 13%) and BIA (aHR = 2.76; PAF = 14%). In HIV-M+F- couples, the man being uncircumcised. with foreskin smegma. was associated with the woman's seroconversion (aHR = 3.16) relative to being circumcised. In F+M- couples, uncircumcised men with BIA had an increased hazard of seroconversion (aHR = 13.03 with smegma and 4.95 without) relative to being circumcised. Self-reporting of symptoms was low for ulcerative and non-ulcerative STIs.

Conclusions

Our findings confirm the role of STIs and highlight the contribution of non-specific genital inflammation to both male-to-female and female-to-male HIV transmission/acquisition risk. Studies are needed to characterize pathogenesis of non-specific inflammation including inguinal adenopathy. A better understanding of genital practices could inform interventions.

Opportunities and Challenges for Environmental Exposure Assessment in Population-Based Studies

A growing number and increasing diversity of factors are available for epidemiological studies. These measures provide new avenues for discovery and prevention, yet they also raise many challenges for adoption in epidemiological investigations. Here, we evaluate 1) designs to investigate diseases that consider heterogeneous and multidimensional indicators of exposure and behavior, 2) the implementation of numerous methods to capture indicators of exposure, and 3) the analytical methods required for discovery and validation. We find that case-control studies have provided insights into genetic susceptibility but are insufficient for characterizing complex effects of environmental factors on disease development. Prospective and two-phase designs are required but must balance extended data collection with follow-up of study participants. We discuss innovations in assessments including the microbiome; mass spectrometry and metabolomics; behavioral assessment; dietary, physical activity, and occupational exposure assessment; air pollution monitoring; and global positioning and individual sensors. We claim the the availability of extensive correlated data raises new challenges in disentangling specific exposures that influence cancer risk from among extensive and often correlated exposures. In conclusion, new high-dimensional exposure assessments offer many new opportunities for environmental assessment in cancer development. Cancer Epidemiol Biomarkers Prev; 26(9); 1370-80. ©2017 AACR.

Comparison of antibiotic supplementation versus a yeast-based prebiotic on the cecal microbiome of commercial broilers

Prebiotics are defined as fermentable food ingredients that selectively stimulate beneficial bacteria in the lower gastrointestinal tract of the host. The purpose of this study was to assess growth performance of broilers and the cecal microbial populations of an antibiotic, BMD50, supplemented birds compared to broiler chickens fed the prebiotic, Biolex^® MB40. Weight response data including feed conversion ratios (FCR), carcasses without giblets (WOG), wing, skin, white meat were collected during processing. Extracted DNA from cecal contents was utilized for microbiome analysis via an Illumina Miseq. In conclusion, white meat yield of Biolex^® MB40 supplemented group exhibited significant improvement compared to both negative control (NC) and BMD50 supplemented groups. In addition, antibiotic significantly decreased level of Lactobacillus in 2 wk compared to other groups. A significantly higher percentage of Campylobacter was observed from the 4 wk old birds treated with antibiotic BMD50 compared to the NC and prebiotic group. Retention of broiler performance and improvement of white meat yield suggest that the prebiotic MB40 appears to be a potential alternative to replace the antibiotic growth promoter.

Insights into study design and statistical analyses in translational microbiome studies

Research questions in translational microbiome studies are substantially more complex than their counterparts in basic science. Robust study designs with appropriate statistical analysis frameworks are pivotal to the success of these translational studies. This review considers how study designs can account for heterogeneous phenotypes by adopting representative sampling schemes for recruiting the study population and making careful choices about the control population. Advantages and limitations of 16S profiling and whole-genome sequencing, the two primary techniques for measuring the microbiome, are discussed followed by an overview of bioinformatic processing of high-throughput sequencing data from these measurements. Practical insights into the downstream statistical analyses including data processing and integration, variable transformations, and data exploration are provided. The merits of regularization and ensemble modeling for analyzing microbiome data are discussed along with a recommendation for selecting modeling approaches based on data-driven simulations and objective evaluation. The review builds on several recent discussions of study design issues in microbiome research but with a stronger emphasis on the downstream and often-ignored aspects of statistical analyses that are crucial for bridging the gap between basic science and translation.

Maternal-Child Microbiome: Specimen Collection, Storage, and Implications for Research and Practice

BACKGROUND

The maternal microbiome is a key contributor to the development and outcomes of pregnancy and the health status of both mother and infant. Significant advances are occurring in the science of the maternal and child microbiome and hold promise in improving outcomes related to pregnancy complications, child development, and chronic health conditions of mother and child.

OBJECTIVES

The purpose of this study was to review site-specific considerations in the collection and storage of maternal and child microbiome samples and its implications for nursing research and practice.

APPROACH

Microbiome sampling protocols were reviewed and synthesized. Precautions across sampling protocols were also noted.

RESULTS

Oral, vaginal, gut, placental, and breast milk are viable sources for sampling the maternal and/or child microbiome. Prior to sampling, special considerations need to be addressed related to various factors including current medications, health status, and hygiene practices. Proper storage of samples will avoid degradation of cellular and DNA structures vital for analysis.

DISCUSSION

Changes in the microbiome throughout the perinatal, postpartum, and childhood periods are dramatic and significant to outcomes of the pregnancy and the long-term health of mother and child. Proper sampling techniques are required to produce reliable results from which evidence-based practice recommendations will be built. Ethical and practical issues surrounding study design and protocol development must also be considered when researching vulnerable groups such as pregnant women and infants. Nurses hold the responsibility to both perform the research and to translate findings from microbiome investigations for clinical use.

Optimizing methods and dodging pitfalls in microbiome research

Research on the human microbiome has yielded numerous insights into health and disease, but also has resulted in a wealth of experimental artifacts. Here, we present suggestions for optimizing experimental design and avoiding known pitfalls, organized in the typical order in which studies are carried out. We first review best practices in experimental design and introduce common confounders such as age, diet, antibiotic use, pet ownership, longitudinal instability, and microbial sharing during cohousing in animal studies. Typically, samples will need to be stored, so we provide data on best practices for several sample types. We then discuss design and analysis of positive and negative controls, which should always be run with experimental samples. We introduce a convenient set of non-biological DNA sequences that can be useful as positive controls for high-volume analysis. Careful analysis of negative and positive controls is particularly important in studies of samples with low microbial biomass, where contamination can comprise most or all of a sample. Lastly, we summarize approaches to enhancing experimental robustness by careful control of multiple comparisons and to comparing discovery and validation cohorts. We hope the experimental tactics summarized here will help researchers in this exciting field advance their studies efficiently while avoiding errors.

Distinct roles for dietary lipids and Porphyromonas gingivalis infection on atherosclerosis progression and the gut microbiota

Mounting evidence in humans supports an etiological role for the microbiota in inflammatory atherosclerosis. Atherosclerosis is a progressive disease characterized by accumulation of inflammatory cells and lipids in vascular tissue. While retention of lipoprotein into the sub-endothelial vascular layer is believed to be the initiating stimulus leading to the development of atherosclerosis, activation of multiple pathways related to vascular inflammation and endothelial dysfunction sustain the process by stimulating recruitment of leukocytes and immune cells into the sub-endothelial layer. The Gram-negative oral pathogen Porphyromonas gingivalis has been associated with the development and acceleration of atherosclerosis in humans and these observations have been validated in animal models. It has been proposed that common mechanisms of immune signaling link stimulation by lipids and pathogens to vascular inflammation. Despite the common outcome of P. gingivalis and lipid feeding on atherosclerosis progression, we established that these pro-atherogenic stimuli induced distinct gene signatures in the ApoE^-/- mouse model of atherosclerosis. In this study, we further defined the distinct roles of dietary lipids and P. gingivalis infection on atherosclerosis progression and the gut microbiota. We demonstrate that diet-induced lipid lowering resulted in less atherosclerotic plaque in ApoE^-/- mice compared to ApoE^-/- mice continuously fed a Western diet. However, the effect of diet-induced lipid lowering on plaque accumulation was blunted by P. gingivalis infection. Using principal component analysis and hierarchical clustering, we demonstrate that dietary intervention as well as P. gingivalis infection result in distinct bacterial communities in fecal and cecal samples of ApoE^-/- mice as compared to ApoE^-/- mice continuously fed either a Western diet or a normal chow diet. Collectively, we identified distinct microbiota changes accompanying atherosclerotic plaque, suggesting a future avenue for investigation on the impact of the gut microbiota, diet, and P. gingivalis infection on atherosclerosis.

Microbiota, Immune Subversion, and Chronic Inflammation

Several host-adapted pathogens and commensals have evolved mechanisms to evade the host innate immune system inducing a state of low-grade inflammation. Epidemiological studies have also documented the association of a subset of these microorganisms with chronic inflammatory disorders. In this review, we summarize recent studies demonstrating the role of the microbiota in chronic inflammatory diseases and discuss how specific microorganisms subvert or inhibit protective signaling normally induced by toll-like receptors (TLRs). We highlight our work on the oral pathogen Porphyromonas gingivalis and discuss the role of microbial modulation of lipid A structures in evasion of TLR4 signaling and resulting systemic immunopathology associated with atherosclerosis. P. gingivalis intrinsically expresses underacylated lipid A moieties and can modify the phosphorylation of lipid A, leading to altered TLR4 signaling. Using P. gingivalis mutant strains expressing distinct lipid A moieties, we demonstrated that expression of antagonist lipid A was associated with P. gingivalis-mediated systemic inflammation and immunopathology, whereas strains expressing agonist lipid A exhibited modest systemic inflammation. Likewise, mice deficient in TLR4 were more susceptible to vascular inflammation after oral infection with P. gingivalis wild-type strain compared to mice possessing functional TLR4. Collectively, our studies support a role for P. gingivalis-mediated dysregulation of innate and adaptive responses resulting in immunopathology and systemic inflammation. We propose that anti-TLR4 interventions must be designed with caution, given the balance between the protective and destructive roles of TLR signaling in response to microbiota and associated immunopathologies.

Microbiome Datasets Are Compositional: And This Is Not Optional

Datasets collected by high-throughput sequencing (HTS) of 16S rRNA gene amplimers, metagenomes or metatranscriptomes are commonplace and being used to study human disease states, ecological differences between sites, and the built environment. There is increasing awareness that microbiome datasets generated by HTS are compositional because they have an arbitrary total imposed by the instrument. However, many investigators are either unaware of this or assume specific properties of the compositional data. The purpose of this review is to alert investigators to the dangers inherent in ignoring the compositional nature of the data, and point out that HTS datasets derived from microbiome studies can and should be treated as compositions at all stages of analysis. We briefly introduce compositional data, illustrate the pathologies that occur when compositional data are analyzed inappropriately, and finally give guidance and point to resources and examples for the analysis of microbiome datasets using compositional data analysis.