Experiences and lessons learned from two virtual, hands-on microbiome bioinformatics workshops.

In October of 2020, in response to the Coronavirus Disease 2019 (COVID-19) pandemic, our team hosted our first fully online workshop teaching the QIIME 2 microbiome bioinformatics platform. We had 75 enrolled participants who joined from at least 25 different countries on 6 continents, and we had 22 instructors on 4 continents. In the 5-day workshop, participants worked hands-on with a cloud-based shared compute cluster that we deployed for this course. The event was well received, and participants provided feedback and suggestions in a postworkshop questionnaire. In January of 2021, we followed this workshop with a second fully online workshop, incorporating lessons from the first. Here, we present details on the technology and protocols that we used to run these workshops, focusing on the first workshop and then introducing changes made for the second workshop. We discuss what worked well, what didn't work well, and what we plan to do differently in future workshops.

The effects of voluntary wheel running on neuroinflammatory status: Role of monocyte chemoattractant protein-1.

The health benefits of exercise and physical activity (PA) have been well researched and it is widely accepted that PA is crucial for maintaining health. One of the mechanisms by which exercise and PA exert their beneficial effects is through peripheral immune system adaptations. To date, very few studies have looked at the regulation of neuroimmune reactions in response to PA. We studied the effect of voluntary wheel running (VWR) on pro- and anti-inflammatory cytokine levels, patterns of glial cell activation and expression of immune receptors in the brains of female C57BL/6 mice. By using homozygous monocyte chemoattractant protein (MCP)-1 null mice, we investigated the role of this key immunoregulatory cytokine in mediating VWR-induced neuroinflammatory responses. We demonstrated that, compared to their sedentary counterparts, C57BL/6 mice exposed for seven weeks to VWR had increased levels of pro- and anti-inflammatory cytokines, markers of glial cell activation and a trend towards increased expression of toll-like receptor (TLR) 4 in the brain. Measurements of serum cytokines revealed that the alterations in brain cytokine levels could not be explained by the effects of PA on peripheral cytokine levels. We propose that the modified neuroimmune status observed in the VWR group represents an activated immune system, as opposed to a less activated immune system in the sedentary group. Since MCP-1 knockout mice displayed differing patterns of pro- and anti-inflammatory brain cytokine expression and glial activation when compared to their wild-type counterparts, we concluded that the effects of VWR on neuroimmune reactions may be modulated by MCP-1. These identified immunomodulatory effects of PA in the brain could contribute to the observed positive relationship between physically active lifestyles and a reduced risk for a number of neurodegenerative diseases that possess a significant neuroinflammatory component.

Medication Use is Associated with Distinct Microbial Features in Anxiety and Depression.

This study investigated the relationship between gut microbiota and neuropsychiatric disorders (NPDs), specifically anxiety disorder (ANXD) and/or major depressive disorder (MDD), as defined by DSM-IV or V criteria. The study also examined the influence of medication use, particularly antidepressants and/or anxiolytics, classified through the Anatomical Therapeutic Chemical (ATC) Classification System, on the gut microbiota. Both 16S rRNA gene amplicon sequencing and shallow shotgun sequencing were performed on DNA extracted from 666 fecal samples from the Tulsa-1000 and NeuroMAP CoBRE cohorts. The results highlight the significant influence of medication use; antidepressant use is associated with significant differences in gut microbiota beta diversity and has a larger effect size than NPD diagnosis. Next, specific microbes were associated with ANXD and MDD, highlighting their potential for non-pharmacological intervention. Finally, the study demonstrated the capability of Random Forest classifiers to predict diagnoses of NPD and medication use from microbial profiles, suggesting a promising direction for the use of gut microbiota as biomarkers for NPD. The findings suggest that future research on the gut microbiota's role in NPD and its interactions with pharmacological treatments are needed.

Whole-body metabolic modelling reveals microbiome and genomic interactions on reduced urine formate levels in Alzheimer's disease.

In this study, we aimed to understand the potential role of the gut microbiome in the development of Alzheimer's disease (AD). We took a multi-faceted approach to investigate this relationship. Urine metabolomics were examined in individuals with AD and controls, revealing decreased formate and fumarate concentrations in AD. Additionally, we utilised whole-genome sequencing (WGS) data obtained from a separate group of individuals with AD and controls. This information allowed us to create and investigate host-microbiome personalised whole-body metabolic models. Notably, AD individuals displayed diminished formate microbial secretion in these models. Additionally, we identified specific reactions responsible for the production of formate in the host, and interestingly, these reactions were linked to genes that have correlations with AD. This study suggests formate as a possible early AD marker and highlights genetic and microbiome contributions to its production. The reduced formate secretion and its genetic associations point to a complex connection between gut microbiota and AD. This holistic understanding might pave the way for novel diagnostic and therapeutic avenues in AD management.

Clinical consequences of diet-induced dysbiosis.

Various disease states are associated with an imbalance of protective and pathogenic bacteria in the gut, termed dysbiosis. Current evidence reveals that dietary factors affect the microbial ecosystem in the gut. Changes to community structure of the intestinal microbiota are not without consequence considering the wide effects that the microbes have on both local and systemic immunity. The goal of this review is to give insight into the importance of gut microbiota in disease development and the possible therapeutic interventions in clinical settings. We introduce the complex tripartite relationship between diet, microbes and the gut epithelium. This is followed by a summary of clinical evidence of diet-induced dysbiosis as a contributing factor in the development of gastrointestinal diseases like inflammatory bowel disease, irritable bowel syndrome and colorectal cancer, as well as systemic diseases like obesity, diabetes, atherosclerosis and nonalcoholic fatty liver disease. Finally, the current dietary and microbial interventions to promote a healthy microbial profile will be reviewed.

BIRDMAn: A Bayesian differential abundance framework that enables robust inference of host-microbe associations.

Quantifying the differential abundance (DA) of specific taxa among experimental groups in microbiome studies is challenging due to data characteristics (e.g., compositionality, sparsity) and specific study designs (e.g., repeated measures, meta-analysis, cross-over). Here we present BIRDMAn (Bayesian Inferential Regression for Differential Microbiome Analysis), a flexible DA method that can account for microbiome data characteristics and diverse experimental designs. Simulations show that BIRDMAn models are robust to uneven sequencing depth and provide a >20-fold improvement in statistical power over existing methods. We then use BIRDMAn to identify antibiotic-mediated perturbations undetected by other DA methods due to subject-level heterogeneity. Finally, we demonstrate how BIRDMAn can construct state-of-the-art cancer-type classifiers using The Cancer Genome Atlas (TCGA) dataset, with substantial accuracy improvements over random forests and existing DA tools across multiple sequencing centers. Collectively, BIRDMAn extracts more informative biological signals while accounting for study-specific experimental conditions than existing approaches.

Association of Subjective and Objective Measures of Sleep With Gut Microbiota Composition and Diversity in Older Men: The Osteoporotic Fractures in Men Study.

BACKGROUND: Growing evidence suggests bidirectional links between gut microbiota and sleep quality as shared contributors to health. Little is known about the relationship between microbiota and sleep among older persons. METHODS: We used 16S rRNA sequencing to characterize stool microbiota among men (n = 606, mean [standard deviation] age = 83.9 [3.8]) enrolled in the Osteoporotic Fractures in Men (MrOS) study from 2014 to 2016. Sleep was assessed concurrently by a questionnaire (Pittsburgh Sleep Quality index [PSQI]), and activity monitor to examine timing (acrophase) and regularity of patterns (F-statistic). Alpha diversity was measured using Faith's phylogenetic diversity (PD). Beta diversity was calculated with robust Aitchison distance with matrix completion (RPCA) and phylogenetic-RPCA (PRPCA). Their association with sleep variables was tested with partial distance-based redundancy analysis (dbRDA). Predictive-ratio biomarkers associated with sleep measurements were identified with CoDaCoRe. RESULTS: In unadjusted analyses, men with poor sleep (PSQI >5) tended to have lower alpha diversity compared to men with normal sleep (Faith's PD, beta = -0.15; 95% confidence interval [CI]: -0.30 to 0.01, p = .06). Sleep regularity was significantly associated with RPCA and PRPCA, even after adjusting for site, batch, age, ethnicity, body mass index, diabetes, antidepressant and sleep medication use, and health behaviors (RPCA/PRPCA dbRDA; p = .033/.002). In taxonomic analysis, ratios of 7:6 bacteria for better regularity (p = .0004) and 4:7 for worse self-reported sleep (p = .005) were differentially abundant: some butyrate-producing bacteria were associated with better sleep characteristics. CONCLUSIONS: Subjective and objective indicators of sleep quality suggest that older men with better sleep patterns are more likely to harbor butyrate-producing bacteria associated with better health.

A Mediterranean Diet Pattern Improves Intestinal Inflammation Concomitant with Reshaping of the Bacteriome in Ulcerative Colitis: A Randomised Controlled Trial.

BACKGROUND AND AIMS: Dietary patterns are important in managing ulcerative colitis [UC], given their influence on gut microbiome-host symbiosis and inflammation. We investigated whether the Mediterranean Diet Pattern [MDP] vs the Canadian Habitual Diet Pattern [CHD] would affect disease activity, inflammation, and the gut microbiome in patients with quiescent UC. METHODS: We performed a prospective, randomised, controlled trial in adults [65% female; median age 47 years] with quiescent UC in an outpatient setting from 2017 to 2021. Participants were randomised to an MDP [n = 15] or CHD [n = 13] for 12 weeks. Disease activity [Simple Clinical Colitis Activity Index] and faecal calprotectin [FC] were measured at baseline and week 12. Stool samples were analysed by 16S rRNA gene amplicon sequencing. RESULTS: The diet was well tolerated by the MDP group. At week 12, 75% [9/12] of participants in the CHD had an FC >100 µg/g, vs 20% [3/15] of participants in the MDP group. The MDP group had higher levels of total faecal short chain fatty acids [SCFAs] [p = 0.01], acetic acid [p = 0.03], and butyric acid [p = 0.03] compared with the CHD. Furthermore, the MDP induced alterations in microbial species associated with a protective role in colitis [Alistipes finegoldii and Flavonifractor plautii], as well as the production of SCFAs [Ruminococcus bromii]. CONCLUSIONS: An MDP induces gut microbiome alterations associated with the maintenance of clinical remission and reduced FC in patients with quiescent UC. The data support that the MDP is a sustainable diet pattern that could be recommended as a maintenance diet and adjunctive therapy for UC patients in clinical remission. ClinicalTrials.gov no: NCT0305371.

Whole-body modelling reveals microbiome and genomic interactions on reduced urine formate levels in Alzheimer's disease.

In this study, we aimed to understand the potential role of the gut microbiome in the development of Alzheimer's disease (AD). We took a multi-faceted approach to investigate this relationship. Urine metabolomics were examined in individuals with AD and controls, revealing decreased formate and fumarate concentrations in AD. Additionally, we utilized whole-genome sequencing (WGS) data obtained from a separate group of individuals with AD and controls. This information allowed us to create and investigate host-microbiome personalized models. Notably, AD individuals displayed diminished formate microbial secretion in these models. Additionally, we identified specific reactions responsible for the production of formate in the host, and interestingly, these reactions were linked to genes that have correlations with AD. This study suggests formate as a possible early AD marker and highlights genetic and microbiome contributions to its production. The reduced formate secretion and its genetic associations point to a complex connection between gut microbiota and AD. This holistic understanding might pave the way for novel diagnostic and therapeutic avenues in AD management.

A Mediterranean-like fat blend protects against the development of severe colitis in the mucin-2 deficient murine model.

There is a growing appreciation that the interaction between diet, the gut microbiota and the immune system contribute to the development and progression of inflammatory bowel disease (IBD). A mounting body of scientific evidence suggests that high-fat diets exacerbate IBD; however, there is a lack of information on how specific types of fat impact colitis. The Mediterranean diet (MD) is considered a health-promoting diet containing approximately 40% total fat. It is not known if the blend of fats found in the MD contributes to its beneficial protective effects.Mice deficient in the mucin 2 gene (Muc 2-/-) were weaned to 40% fat, isocaloric, isonitrogenous diets. We compared the MD fat blend (high monounsaturated, 2:1 n-6:n-3 polyunsaturated and moderate saturated fat) to diets composed of corn oil (CO, n-6 polyunsaturated-rich), olive oil (monounsaturated-rich) or milk fat (MF, saturated-rich) on spontaneous colitis development in Muc2-/- mice. The MD resulted in lower clinical and histopathological scores and induced tolerogenic CD103+ CD11b+ dendritic, Th22 and IL-17+ IL-22+ cells necessary for intestinal barrier repair. The MD was associated with beneficial microbes and associated with higher cecal acetic acid levels negatively correlated with colitogenic microbes like Akkermansia muciniphila. In contrast, CO showed a higher prevalence of mucin-degraders including A. muciniphila and Enterobacteriaceae, which have been associated with colitis.A dietary blend of fats mimicking the MD, reduces disease activity, inflammation-related biomarkers and improves metabolic parameters in the Muc2-/- mouse model. Our findings suggest that the MD fat blend could be incorporated into a maintenance diet for colitis.

Impact of Vaginal Estrogen on the Urobiome in Postmenopausal Women With Recurrent Urinary Tract Infection.

OBJECTIVE: The aim of this study was to describe effects of vaginal estrogen (VE) on the urogenital microbiome in postmenopausal women with recurrent urinary tract infections (rUTIs). METHODS: This is a secondary analysis of 17 participants enrolled in a randomized controlled trial of VE versus placebo on urinary tract infection recurrence in postmenopausal women with rUTIs. Paired clean-catch urine samples were collected at baseline and after 6 months of VE and sequenced using 16S rRNA gene sequencing. Sequence reads were analyzed using Quantitative Insights Into Microbial Ecology 2. Changes in α diversity, ß diversity, and differentially abundant genera were measured between paired baseline and 6-month samples and between those with a urinary tract infection at 6 months (failures) and those without (successes). RESULTS: Of the 17 women, 11 were successes and 6 were failures after 6 months of VE treatment. There was a significant change in α diversity from baseline to month 6 in samples overall (Kruskal-Wallis χ2 = 3.47, P = 0.037) and in the treatment success group (Yuen T = -2.53, P = 0.035). The increase in relative abundance of Lactobacillus crispatus, Lactobacillus gasseri, and Lactobacillus iners AB-1 was correlated with month 6. A relative bloom of L. crispatus compared with L. gasseri was associated with treatment success (Kruskal-Wallis χ2 = 4.9, P = 0.0014). CONCLUSIONS: Lactobacillus increases in the urogenital microbiome of postmenopausal women with rUTI after 6 months of VE. However, only the relative increase in L. crispatus specifically may be associated with treatment success.

Swapping Metagenomics Preprocessing Pipeline Components Offers Speed and Sensitivity Increases.

Increasing data volumes on high-throughput sequencing instruments such as the NovaSeq 6000 leads to long computational bottlenecks for common metagenomics data preprocessing tasks such as adaptor and primer trimming and host removal. Here, we test whether faster recently developed computational tools (Fastp and Minimap2) can replace widely used choices (Atropos and Bowtie2), obtaining dramatic accelerations with additional sensitivity and minimal loss of specificity for these tasks. Furthermore, the taxonomic tables resulting from downstream processing provide biologically comparable results. However, we demonstrate that for taxonomic assignment, Bowtie2's specificity is still required. We suggest that periodic reevaluation of pipeline components, together with improvements to standardized APIs to chain them together, will greatly enhance the efficiency of common bioinformatics tasks while also facilitating incorporation of further optimized steps running on GPUs, FPGAs, or other architectures. We also note that a detailed exploration of available algorithms and pipeline components is an important step that should be taken before optimization of less efficient algorithms on advanced or nonstandard hardware. IMPORTANCE In shotgun metagenomics studies that seek to relate changes in microbial DNA across samples, processing the data on a computer often takes longer than obtaining the data from the sequencing instrument. Recently developed software packages that perform individual steps in the pipeline of data processing in principle offer speed advantages, but in practice they may contain pitfalls that prevent their use, for example, they may make approximations that introduce unacceptable errors in the data. Here, we show that differences in choices of these components can speed up overall data processing by 5-fold or more on the same hardware while maintaining a high degree of correctness, greatly reducing the time taken to interpret results. This is an important step for using the data in clinical settings, where the time taken to obtain the results may be critical for guiding treatment.

Individuals with substance use disorders have a distinct oral microbiome pattern.

BACKGROUND: Substance use disorder emerges from a complex interaction between genetic predisposition, life experiences, exposure, and subsequent adaptation of biological systems to the repeated use of drugs. Recently, investigators have proposed that the human microbiota may play a role in brain health and disease. In particular, the human oral microbiome is a distinct and diverse ecological niche with its composition influenced by external factors such as lifestyle, diet, and oral hygiene. This investigation examined whether individuals with substance use disorder (SU) show a different oral microbiome pattern and whether this pattern is sufficient to delineate the SU group from healthy comparison (HC) subjects. METHODS: Participants were a sub-sample (N â€‹= â€‹177) of the Tulsa 1000 (T-1000) project. We analyzed 123 SU and 54 HC subjects using 16S rRNA marker gene sequencing to characterize the oral microbiome. RESULTS: The groups differed significantly based on the UniFrac distance, a phylogenetic-based measure of beta diversity, but did not differ in alpha diversity. Using a machine learning approach, microbiome features combined with socio-demographic variables successfully categorized group membership with 87%-92% accuracy, even after controlling for external factors such as smoking or alcohol consumption. SU individuals with relatively lower diversity also reported higher levels of negative reinforcement experiences associated with their primary substance of abuse. CONCLUSIONS: Oral microbiome features are useful to sufficiently differentiate SU from HC subjects. There is some evidence that subjects whose drug use is driven by negative reinforcement show an impoverished oral microbiome. Taken together, the oral microbiome may help to understand the dysfunctional biological processes that promote substance use or may be pragmatically useful as a risk or severity biological marker.

Candidate probiotic Lactiplantibacillus plantarum HNU082 rapidly and convergently evolves within human, mice, and zebrafish gut but differentially influences the resident microbiome.

BACKGROUND: Improving probiotic engraftment in the human gut requires a thorough understanding of the in vivo adaptive strategies of probiotics in diverse contexts. However, for most probiotic strains, these in vivo genetic processes are still poorly characterized. Here, we investigated the effects of gut selection pressures from human, mice, and zebrafish on the genetic stability of a candidate probiotic Lactiplantibacillus plantarum HNU082 (Lp082) as well as its ecological and evolutionary impacts on the indigenous gut microbiota using shotgun metagenomic sequencing in combination with isolate resequencing methods. RESULTS: We combined both metagenomics and isolate whole genome sequencing approaches to systematically study the gut-adaptive evolution of probiotic L. plantarum and the ecological and evolutionary changes of resident gut microbiomes in response to probiotic ingestion in multiple host species. Independent of host model, Lp082 colonized and adapted to the gut by acquiring highly consistent single-nucleotide mutations, which primarily modulated carbohydrate utilization and acid tolerance. We cultivated the probiotic mutants and validated that these gut-adapted mutations were genetically stable for at least 3 months and improved their fitness in vitro. In turn, resident gut microbial strains, especially competing strains with Lp082 (e.g., Bacteroides spp. and Bifidobacterium spp.), actively responded to Lp082 engraftment by accumulating 10-70 times more evolutionary changes than usual. Human gut microbiota exhibited a higher ecological and genetic stability than that of mice. CONCLUSIONS: Collectively, our results suggest a highly convergent adaptation strategy of Lp082 across three different host environments. In contrast, the evolutionary changes within the resident gut microbes in response to Lp082 were more divergent and host-specific; however, these changes were not associated with any adverse outcomes. This work lays a theoretical foundation for leveraging animal models for ex vivo engineering of probiotics to improve engraftment outcomes in humans. Video abstract.

Compositional and genetic alterations in Graves' disease gut microbiome reveal specific diagnostic biomarkers.

Graves' Disease is the most common organ-specific autoimmune disease and has been linked in small pilot studies to taxonomic markers within the gut microbiome. Important limitations of this work include small sample sizes and low-resolution taxonomic markers. Accordingly, we studied 162 gut microbiomes of mild and severe Graves' disease (GD) patients and healthy controls. Taxonomic and functional analyses based on metagenome-assembled genomes (MAGs) and MAG-annotated genes, together with predicted metabolic functions and metabolite profiles, revealed a well-defined network of MAGs, genes and clinical indexes separating healthy from GD subjects. A supervised classification model identified a combination of biomarkers including microbial species, MAGs, genes and SNPs, with predictive power superior to models from any single biomarker type (AUC = 0.98). Global, cross-disease multi-cohort analysis of gut microbiomes revealed high specificity of these GD biomarkers, notably discriminating against Parkinson's Disease, and suggesting that non-invasive stool-based diagnostics will be useful for these diseases.

A comparison of DNA/RNA extraction protocols for high-throughput sequencing of microbial communities.

One goal of microbial ecology researchers is to capture the maximum amount of information from all organisms in a sample. The recent COVID-19 pandemic, caused by the RNA virus SARS-CoV-2, has highlighted a gap in traditional DNA-based protocols, including the high-throughput methods the authors previously established as field standards. To enable simultaneous SARS-CoV-2 and microbial community profiling, the authors compared the relative performance of two total nucleic acid extraction protocols with the authors' previously benchmarked protocol. The authors included a diverse panel of environmental and host-associated sample types, including body sites commonly swabbed for COVID-19 testing. Here the authors present results comparing the cost, processing time, DNA and RNA yield, microbial community composition, limit of detection and well-to-well contamination between these protocols.

EMPress Enables Tree-Guided, Interactive, and Exploratory Analyses of Multi-omic Data Sets.

Standard workflows for analyzing microbiomes often include the creation and curation of phylogenetic trees. Here we present EMPress, an interactive web tool for visualizing trees in the context of microbiome, metabolome, and other community data scalable to trees with well over 500,000 nodes. EMPress provides novel functionality-including ordination integration and animations-alongside many standard tree visualization features and thus simplifies exploratory analyses of many forms of 'omic data.IMPORTANCE Phylogenetic trees are integral data structures for the analysis of microbial communities. Recent work has also shown the utility of trees constructed from certain metabolomic data sets, further highlighting their importance in microbiome research. The ever-growing scale of modern microbiome surveys has led to numerous challenges in visualizing these data. In this paper we used five diverse data sets to showcase the versatility and scalability of EMPress, an interactive web visualization tool. EMPress addresses the growing need for exploratory analysis tools that can accommodate large, complex multi-omic data sets.

Physical Activity Shapes the Intestinal Microbiome and Immunity of Healthy Mice but Has No Protective Effects against Colitis in MUC2-/- Mice.

The interactions among humans, their environment, and the trillions of microbes residing within the human intestinal tract form a tripartite relationship that is fundamental to the overall health of the host. Disruptions in the delicate balance between the intestinal microbiota and host immunity are implicated in various chronic diseases, including inflammatory bowel disease (IBD). There is no known cure for IBD; therefore, novel therapeutics targeting prevention and symptom management are of great interest. Recently, physical activity in healthy mice was shown to be protective against chemically induced colitis; however, the benefits of physical activity during or following disease onset are not known. In this study, we examine whether voluntary wheel running is protective against primary disease symptoms in a mucin 2-deficient (Muc2-/- ) lifelong model of murine colitis. We show that 6 weeks of wheel running in healthy C57BL/6 mice leads to distinct changes in fecal bacteriome, increased butyrate production, and modulation in colonic gene expression of various cytokines, suggesting an overall primed anti-inflammatory state. However, these physical activity-derived benefits are not present in Muc2-/- mice harboring a dysfunctional mucosal layer from birth, ultimately showing no improvements in clinical signs. We extrapolate from our findings that while physical activity in healthy individuals may be an important preventative measure against IBD, for those with a compromised intestinal mucosa, a commonality in IBD patients, these benefits are lost.IMPORTANCE Perturbation in the gut microbial ecosystem has been associated with various diseases, including inflammatory bowel disease. Habitual physical activity, through its ability to modulate the gut microbiome, has recently been shown to prophylactically protect against chemically induced models of murine colitis. Here, we (i) confirm previous reports that physical activity has limited but significant effects on the gut microbiome of mice and (ii) show that such changes are associated with anti-inflammatory states in the gut, such as increased production of beneficial short-chain fatty acids and lower levels of proinflammatory immune markers implicated in human colitis; however, we also show that (iii) these physical activity-derived benefits are completely lost in the absence of a healthy intestinal mucus layer, a hallmark phenotype of human colitis.

Fish oil supplementation reduces maternal defensive inflammation and predicts a gut bacteriome with reduced immune priming capacity in infants.

Habitual supplementation of fish oil is thought to provide benefits to the developing infant; however, the effects on infant microbial establishment and immune development are unknown. A 6-month observational cohort study was conducted where 47 out of 91 women self-administered dietary fish oil during breastfeeding. Infant stool and mothers' breast milk were collected each month over 6 months. Gas chromatography was used to quantify breast milk fatty acids and high-throughput sequencing was used to assess the infant fecal microbiota. Immune markers and parent-reported questionnaires were used to assess infant immunity and health up to 2 years. Our results reveal that fish oil supplementation decreased secretory immunoglobulin A and increased IL-10 production in lactating women along with increased breast milk eicosapentaenoic acid, and this corresponded to increased abundances of fecal Bifidobacterium and Lactobacillus spp. in their infants. Docosahexaenoic acid levels in breast milk aligned with decreases in infant gut bacterial richness and the predicted bacterial phenotypes suggested that fish oil lowers commensal traits involved in pathogen colonization resistance. Despite this, there were no differences in sickness incidence in toddlers. This study revealed that fish oil associates with decreases in breast milk defensive inflammatory responses and corresponds with infant fecal microbiota with anti-inflammatory potential.

QIIME 2 Enables Comprehensive End-to-End Analysis of Diverse Microbiome Data and Comparative Studies with Publicly Available Data.

QIIME 2 is a completely re-engineered microbiome bioinformatics platform based on the popular QIIME platform, which it has replaced. QIIME 2 facilitates comprehensive and fully reproducible microbiome data science, improving accessibility to diverse users by adding multiple user interfaces. QIIME 2 can be combined with Qiita, an open-source web-based platform, to re-use available data for meta-analysis. The following basic protocol describes how to install QIIME 2 on a single computer and analyze microbiome sequence data, from processing of raw DNA sequence reads through generating publishable interactive figures. These interactive figures allow readers of a study to interact with data with the same ease as its authors, advancing microbiome science transparency and reproducibility. We also show how plug-ins developed by the community to add analysis capabilities can be installed and used with QIIME 2, enhancing various aspects of microbiome analyses-e.g., improving taxonomic classification accuracy. Finally, we illustrate how users can perform meta-analyses combining different datasets using readily available public data through Qiita. In this tutorial, we analyze a subset of the Early Childhood Antibiotics and the Microbiome (ECAM) study, which tracked the microbiome composition and development of 43 infants in the United States from birth to 2 years of age, identifying microbiome associations with antibiotic exposure, delivery mode, and diet. For more information about QIIME 2, see https://qiime2.org. To troubleshoot or ask questions about QIIME 2 and microbiome analysis, join the active community at https://forum.qiime2.org. © 2020 The Authors. Basic Protocol: Using QIIME 2 with microbiome data Support Protocol: Further microbiome analyses.