Reproducible acquisition, management and meta-analysis of nucleotide sequence (meta)data using q2-fondue.

MOTIVATION: The volume of public nucleotide sequence data has blossomed over the past two decades and is ripe for re- and meta-analyses to enable novel discoveries. However, reproducible re-use and management of sequence datasets and associated metadata remain critical challenges. We created the open source Python package q2-fondue to enable user-friendly acquisition, re-use and management of public sequence (meta)data while adhering to open data principles. RESULTS: q2-fondue allows fully provenance-tracked programmatic access to and management of data from the NCBI Sequence Read Archive (SRA). Unlike other packages allowing download of sequence data from the SRA, q2-fondue enables full data provenance tracking from data download to final visualization, integrates with the QIIME 2 ecosystem, prevents data loss upon space exhaustion and allows download of (meta)data given a publication library. To highlight its manifold capabilities, we present executable demonstrations using publicly available amplicon, whole genome and metagenome datasets. AVAILABILITY AND IMPLEMENTATION: q2-fondue is available as an open-source BSD-3-licensed Python package at https://github.com/bokulich-lab/q2-fondue. Usage tutorials are available in the same repository. All Jupyter notebooks used in this article are available under https://github.com/bokulich-lab/q2-fondue-examples. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Multi-omics data integration reveals metabolome as the top predictor of the cervicovaginal microenvironment.

Emerging evidence suggests that host-microbe interaction in the cervicovaginal microenvironment contributes to cervical carcinogenesis, yet dissecting these complex interactions is challenging. Herein, we performed an integrated analysis of multiple "omics" datasets to develop predictive models of the cervicovaginal microenvironment and identify characteristic features of vaginal microbiome, genital inflammation and disease status. Microbiomes, vaginal pH, immunoproteomes and metabolomes were measured in cervicovaginal specimens collected from a cohort (n = 72) of Arizonan women with or without cervical neoplasm. Multi-omics integration methods, including neural networks (mmvec) and Random Forest supervised learning, were utilized to explore potential interactions and develop predictive models. Our integrated analyses revealed that immune and cancer biomarker concentrations were reliably predicted by Random Forest regressors trained on microbial and metabolic features, suggesting close correspondence between the vaginal microbiome, metabolome, and genital inflammation involved in cervical carcinogenesis. Furthermore, we show that features of the microbiome and host microenvironment, including metabolites, microbial taxa, and immune biomarkers are predictive of genital inflammation status, but only weakly to moderately predictive of cervical neoplastic disease status. Different feature classes were important for prediction of different phenotypes. Lipids (e.g. sphingolipids and long-chain unsaturated fatty acids) were strong predictors of genital inflammation, whereas predictions of vaginal microbiota and vaginal pH relied mostly on alterations in amino acid metabolism. Finally, we identified key immune biomarkers associated with the vaginal microbiota composition and vaginal pH (MIF), as well as genital inflammation (IL-6, IL-10, MIP-1α).

A communal catalogue reveals Earth's multiscale microbial diversity.

Our growing awareness of the microbial world's importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth's microbial diversity.

Learning representations of microbe-metabolite interactions.

Integrating multiomics datasets is critical for microbiome research; however, inferring interactions across omics datasets has multiple statistical challenges. We solve this problem by using neural networks (https://github.com/biocore/mmvec) to estimate the conditional probability that each molecule is present given the presence of a specific microorganism. We show with known environmental (desert soil biocrust wetting) and clinical (cystic fibrosis lung) examples, our ability to recover microbe-metabolite relationships, and demonstrate how the method can discover relationships between microbially produced metabolites and inflammatory bowel disease.

RESCRIPt: Reproducible sequence taxonomy reference database management.

Nucleotide sequence and taxonomy reference databases are critical resources for widespread applications including marker-gene and metagenome sequencing for microbiome analysis, diet metabarcoding, and environmental DNA (eDNA) surveys. Reproducibly generating, managing, using, and evaluating nucleotide sequence and taxonomy reference databases creates a significant bottleneck for researchers aiming to generate custom sequence databases. Furthermore, database composition drastically influences results, and lack of standardization limits cross-study comparisons. To address these challenges, we developed RESCRIPt, a Python 3 software package and QIIME 2 plugin for reproducible generation and management of reference sequence taxonomy databases, including dedicated functions that streamline creating databases from popular sources, and functions for evaluating, comparing, and interactively exploring qualitative and quantitative characteristics across reference databases. To highlight the breadth and capabilities of RESCRIPt, we provide several examples for working with popular databases for microbiome profiling (SILVA, Greengenes, NCBI-RefSeq, GTDB), eDNA and diet metabarcoding surveys (BOLD, GenBank), as well as for genome comparison. We show that bigger is not always better, and reference databases with standardized taxonomies and those that focus on type strains have quantitative advantages, though may not be appropriate for all use cases. Most databases appear to benefit from some curation (quality filtering), though sequence clustering appears detrimental to database quality. Finally, we demonstrate the breadth and extensibility of RESCRIPt for reproducible workflows with a comparison of global hepatitis genomes. RESCRIPt provides tools to democratize the process of reference database acquisition and management, enabling researchers to reproducibly and transparently create reference materials for diverse research applications. RESCRIPt is released under a permissive BSD-3 license at https://github.com/bokulich-lab/RESCRIPt.

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.

Infant behavioral state and stool microbiome in infants receiving Lactocaseibacillus rhamnosus GG in formula: randomized controlled trial.

BACKGROUND: Our aim was to evaluate infant behavioral state, stool microbiome profile and calprotectin in infants with infantile colic receiving a partially hydrolyzed protein formula with or without added Lacticaseibacillus (formerly Lactobacillus) rhamnosus GG (LGG). METHODS: In this single-center, double-blind, controlled, parallel, prospective study, term infants (14-28 days of age) identified with colic (using modified Wessel's criteria: cried and/or fussed ≥ 3 h/day for ≥ 3 days/week, in a one-week period) were randomized to receive one of two formulas over a three-week feeding period: marketed partially hydrolyzed cow's milk-based infant formula (PHF, n = 35) or a similar formula with added LGG (PHF-LGG, n = 36). Parent-reported infant behavior was recorded at three time points (Study Days 2-4, 10-12, and 18-20). Duration (hours/day) of crying/fussing (averaged over each three-day period) was the primary outcome. Stool samples were collected at Baseline and Study End (Days 19-21) to determine stool LGG colonization (by qPCR) and microbial abundance (using 16S rRNA gene sequencing) and calprotectin (µg/g). RESULTS: Duration of crying/fussing (mean ± SE) decreased and awake/content behavior increased over time with no significant group differences over the course of the study. There were no group differences in the percentage of infants who experienced colic by study end. Colic decreased by Study End vs Baseline in both groups. Change in fecal calprotectin also was similar between groups. Comparing Study End vs Baseline, LGG abundance was greater in the PHF-LGG group (P < 0.001) whereas alpha diversity was greater in the PHF group (P = 0.022). Beta diversity was significantly different between PHF and PHF-LGG at Study End (P = 0.05). By study end, relative abundance of L. rhamnosus was higher in the PHF-LGG vs PHF group and vs Baseline. CONCLUSIONS: In this pilot study of infants with colic, both study formulas were well tolerated. Crying/fussing decreased and awake/content behavior increased in both study groups over the course of the study. Study results demonstrate a successful introduction of the probiotic to the microbiome. The partially hydrolyzed protein formula with added LGG was associated with significant changes in the gut microbiome. TRIAL REGISTRATION: ClinicalTrials.gov, ClinicalTrials.gov Identifier: NCT02340143 . Registered 16/01/2015.

Loss of HDAC6 alters gut microbiota and worsens obesity.

Alterations in gut microbiota are known to affect intestinal inflammation and obesity. Antibiotic treatment can affect weight gain by elimination of histone deacetylase (HDAC) inhibitor-producing microbes, which are anti-inflammatory by augmenting regulatory T (Treg) cells. We asked whether mice that lack HDAC6 and have potent suppressive Treg cells are protected from microbiota-induced accelerated weight gain. We crossed wild-type and HDAC6-deficient mice and subjected the offspring to perinatal penicillin, inducing weight gain via microbiota disturbance. We observed that male HDAC6-deficient mice were not protected and developed profoundly accelerated weight gain. The antibiotic-exposed HDAC6-deficient mice showed a mixed immune phenotype with increased CD4+ and CD8+ T-cell activation yet maintained the enhanced Treg cell-suppressive function phenotype characteristic of HDAC6-deficient mice. 16S rRNA sequencing of mouse fecal samples reveals that their microbiota diverged with time, with HDAC6 deletion altering microbiome composition. On a high-fat diet, HDAC6-deficient mice were depleted in representatives of the S24-7 family and Lactobacillus but enriched with Bacteroides and Parabacteroides; these changes are associated with obesity. Our findings further our understanding of the influence of HDACs on microbiome composition and are important for the development of HDAC6 inhibitors in the treatment of human diseases.-Lieber, A. D., Beier, U. H., Xiao, H., Wilkins, B. J., Jiao, J., Li, X. S., Schugar, R. C., Strauch, C. M., Wang, Z., Brown, J. M., Hazen, S. L., Bokulich, N. A., Ruggles, K. V., Akimova, T., Hancock, W. W., Blaser, M. J. Loss of HDAC6 alters gut microbiota and worsens obesity.

Fecal microbiota and bile acid interactions with systemic and adipose tissue metabolism in diet-induced weight loss of obese postmenopausal women.

BACKGROUND: Microbiota and bile acids in the gastrointestinal tract profoundly alter systemic metabolic processes. In obese subjects, gradual weight loss ameliorates adipose tissue inflammation and related systemic changes. We assessed how rapid weight loss due to a very low calorie diet (VLCD) affects the fecal microbiome and fecal bile acid composition, and their interactions with the plasma metabolome and subcutaneous adipose tissue inflammation in obesity. METHODS: We performed a prospective cohort study of VLCD-induced weight loss of 10% in ten grades 2-3 obese postmenopausal women in a metabolic unit. Baseline and post weight loss evaluation included fasting plasma analyzed by mass spectrometry, adipose tissue transcription by RNA sequencing, stool 16S rRNA sequencing for fecal microbiota, fecal bile acids by mass spectrometry, and urinary metabolic phenotyping by 1H-NMR spectroscopy. Outcome measures included mixed model correlations between changes in fecal microbiota and bile acid composition with changes in plasma metabolite and adipose tissue gene expression pathways. RESULTS: Alterations in the urinary metabolic phenotype following VLCD-induced weight loss were consistent with starvation ketosis, protein sparing, and disruptions to the functional status of the gut microbiota. We show that the core microbiome was preserved during VLCD-induced weight loss, but with changes in several groups of bacterial taxa with functional implications. UniFrac analysis showed overall parallel shifts in community structure, corresponding to reduced abundance of the genus Roseburia and increased Christensenellaceae;g__ (unknown genus). Imputed microbial functions showed changes in fat and carbohydrate metabolism. A significant fall in fecal total bile acid concentration and reduced deconjugation and 7-α-dihydroxylation were accompanied by significant changes in several bacterial taxa. Individual bile acids in feces correlated with amino acid, purine, and lipid metabolic pathways in plasma. Furthermore, several fecal bile acids and bacterial species correlated with altered gene expression pathways in adipose tissue. CONCLUSIONS: VLCD dietary intervention in obese women changed the composition of several fecal microbial populations while preserving the core fecal microbiome. Changes in individual microbial taxa and their functions correlated with variations in the plasma metabolome, fecal bile acid composition, and adipose tissue transcriptome. Trial Registration ClinicalTrials.gov NCT01699906, 4-Oct-2012, Retrospectively registered. URL- https://clinicaltrials.gov/ct2/show/NCT01699906.

Microbial biogeography of wine grapes is conditioned by cultivar, vintage, and climate.

Wine grapes present a unique biogeography model, wherein microbial biodiversity patterns across viticultural zones not only answer questions of dispersal and community maintenance, they are also an inherent component of the quality, consumer acceptance, and economic appreciation of a culturally important food product. On their journey from the vineyard to the wine bottle, grapes are transformed to wine through microbial activity, with indisputable consequences for wine quality parameters. Wine grapes harbor a wide range of microbes originating from the surrounding environment, many of which are recognized for their role in grapevine health and wine quality. However, determinants of regional wine characteristics have not been identified, but are frequently assumed to stem from viticultural or geological factors alone. This study used a high-throughput, short-amplicon sequencing approach to demonstrate that regional, site-specific, and grape-variety factors shape the fungal and bacterial consortia inhabiting wine-grape surfaces. Furthermore, these microbial assemblages are correlated to specific climatic features, suggesting a link between vineyard environmental conditions and microbial inhabitation patterns. Taken together, these factors shape the unique microbial inputs to regional wine fermentations, posing the existence of nonrandom "microbial terroir" as a determining factor in regional variation among wine grapes.

Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing.

High-throughput sequencing has revolutionized microbial ecology, but read quality remains a considerable barrier to accurate taxonomy assignment and α-diversity assessment for microbial communities. We demonstrate that high-quality read length and abundance are the primary factors differentiating correct from erroneous reads produced by Illumina GAIIx, HiSeq and MiSeq instruments. We present guidelines for user-defined quality-filtering strategies, enabling efficient extraction of high-quality data and facilitating interpretation of Illumina sequencing results.

Human milk glycomics and gut microbial genomics in infant feces show a correlation between human milk oligosaccharides and gut microbiota: a proof-of-concept study.

Human milk oligosaccharides (HMOs) play a key role in shaping and maintaining a healthy infant gut microbiota. This article demonstrates the potential of combining recent advances in glycomics and genomics to correlate abundances of fecal microbes and fecal HMOs. Serial fecal specimens from two healthy breast-fed infants were analyzed by bacterial DNA sequencing to characterize the microbiota and by mass spectrometry to determine abundances of specific HMOs that passed through the intestinal tract without being consumed by the luminal bacteria. In both infants, the fecal bacterial population shifted from non-HMO-consuming microbes to HMO-consuming bacteria during the first few weeks of life. An initial rise in fecal HMOs corresponded with bacterial populations composed primarily of non-HMO-consuming Enterobacteriaceae and Staphylococcaeae. This was followed by decreases in fecal HMOs as the proportion of HMO-consuming Bacteroidaceae and Bifidobacteriaceae increased. Analysis of HMO structures with isomer differentiation revealed that HMO consumption is highly structure-specific, with unique isomers being consumed and others passing through the gut unaltered. These results represent a proof-of-concept and are consistent with the highly selective, prebiotic effect of HMOs in shaping the gut microbiota in the first weeks of life. The analysis of selective fecal bacterial substrates as a measure of alterations in the gut microbiota may be a potential marker of dysbiosis.

Microbial biogeography of the transnational fermented milk matsoni.

The fermented milk matsoni is a traditional, national food product of both Georgia and Armenia. Little is known about the effects of biogeography and milk type on the microbial biodiversity of matsoni or the fungal composition of matsoni fermentations. High-throughput marker-gene sequencing was used to survey the bacterial and fungal communities of matsoni from different milk types and regions throughout Armenia and Georgia. Results demonstrate that both production region and milk type influence matsoni microbiota, suggesting that the traditional production methods preserve the transfer of unique regional microbiota from batch to batch. Bacterial profiles were dominated by Lactobacillus and Streptococcus species. Yeast profiles varied dramatically, with Kluyveromyces marxianus, Candida famata, Saccharomyces cerevisiae, Lodderomyces elongisporus, and Kluyveromyces lactis being the most important species distinguishing production regions and milk types. This survey will enable more detailed capture and characterization of specific microbiota detected within these fermentations.

Indigenous bacteria and fungi drive traditional kimoto sake fermentations.

Sake (Japanese rice wine) production is a complex, multistage process in which fermentation is performed by a succession of mixed fungi and bacteria. This study employed high-throughput rRNA marker gene sequencing, quantitative PCR, and terminal restriction fragment length polymorphism to characterize the bacterial and fungal communities of spontaneous sake production from koji to product as well as brewery equipment surfaces. Results demonstrate a dynamic microbial succession, with koji and early moto fermentations dominated by Bacillus, Staphylococcus, and Aspergillus flavus var. oryzae, succeeded by Lactobacillus spp. and Saccharomyces cerevisiae later in the fermentations. The microbiota driving these fermentations were also prevalent in the production environment, illustrating the reservoirs and routes for microbial contact in this traditional food fermentation. Interrogating the microbial consortia of production environments in parallel with food products is a valuable approach for understanding the complete ecology of food production systems and can be applied to any food system, leading to enlightened perspectives for process control and food safety.

Prebiotic oligosaccharides in premature infants.

OBJECTIVE: The aim of the study was to determine the impact of increasing doses of 2 prebiotic oligosaccharides and of an "all-human diet" on the intestinal microbiota of premature infants. METHODS: Twelve premature infants receiving formula feedings were randomly assigned to receive either galacto-oligosaccharide (F+GOS) or a pooled concentrated donor human milk product containing human milk oligosaccharides (F+HMO) in increasing doses during a 5-week period. A second group of 15 premature infants received their mother's own milk fortified with either a concentrated donor human milk product (H+H) or a bovine powdered fortifier (H+B). Serial stool specimens from each infant were analyzed by terminal restriction fragment length polymorphism and quantitative polymerase chain reaction for bacterial composition. RESULTS: All of the infants studied had relatively low levels of bifidobacteria and no measurable Lactobacilli. Infants from the F+GOS and F+HMO groups demonstrated an increase in relative numbers of Clostridia with increasing doses. Compared with the H+B group, the infants in the F+HMO and the H+H groups showed an unexpected trend toward an increase in γ-Proteobacteria over time/dose. Principal coordinate analyses and Shannon diversity scores were not significantly different among the 4 groups. Infants in the H+H group received more antibiotics during the study period than those in the other groups. Two of the infants receiving GOS developed feeding intolerance. CONCLUSIONS: None of the prebiotic interventions resulted in significant increases in bifidobacteria compared with baseline specimens or the H+B group; however, many of the infants did not receive the highest doses of GOS and HMO, and antibiotic use in the H+H group was high.

Surface microbes in the neonatal intensive care unit: changes with routine cleaning and over time.

Premature infants in neonatal intensive care units (NICUs) are highly susceptible to infection due to the immaturity of their immune systems, and nosocomial infections are a significant risk factor for death and poor neurodevelopmental outcome in this population. To investigate the impact of cleaning within a NICU, a high-throughput short-amplicon-sequencing approach was used to profile bacterial and fungal surface communities before and after cleaning. Intensive cleaning of surfaces in contact with neonates decreased the total bacterial load and the percentage of Streptococcus species with similar trends for total fungal load and Staphylococcus species; this may have clinical relevance since staphylococci and streptococci are the most common causes of nosocomial NICU infections. Surfaces generally had low levels of other taxa containing species that commonly cause nosocomial infections (e.g., Enterobacteriaceae) that were not significantly altered with cleaning. Several opportunistic yeasts were detected in the NICU environment, demonstrating that these NICU surfaces represent a potential vector for spreading fungal pathogens. These results underline the importance of routine cleaning as a means of managing the microbial ecosystem of NICUs and of future opportunities to minimize exposures of vulnerable neonates to potential pathogens and to use amplicon-sequencing tools for microbial surveillance and hygienic testing in hospital environments.

Improved selection of internal transcribed spacer-specific primers enables quantitative, ultra-high-throughput profiling of fungal communities.

Ultra-high-throughput sequencing (HTS) of fungal communities has been restricted by short read lengths and primer amplification bias, slowing the adoption of newer sequencing technologies to fungal community profiling. To address these issues, we evaluated the performance of several common internal transcribed spacer (ITS) primers and designed a novel primer set and work flow for simultaneous quantification and species-level interrogation of fungal consortia. Primer comparison and validation were predicted in silico and by sequencing a "mock community" of mixed yeast species to explore the challenges of amplicon length and amplification bias for reconstructing defined yeast community structures. The amplicon size and distribution of this primer set are smaller than for all preexisting ITS primer sets, maximizing sequencing coverage of hypervariable ITS domains by very-short-amplicon, high-throughput sequencing platforms. This feature also enables the optional integration of quantitative PCR (qPCR) directly into the HTS preparatory work flow by substituting qPCR with these primers for standard PCR, yielding quantification of individual community members. The complete work flow described here, utilizing any of the qualified primer sets evaluated, can rapidly profile mixed fungal communities and capably reconstructed well-characterized beer and wine fermentation fungal communities.

Facility-specific "house" microbiome drives microbial landscapes of artisan cheesemaking plants.

Cheese fermentations involve the growth of complex microbial consortia, which often originate in the processing environment and drive the development of regional product qualities. However, the microbial milieus of cheesemaking facilities are largely unexplored and the true nature of the fermentation-facility relationship remains nebulous. Thus, a high-throughput sequencing approach was employed to investigate the microbial ecosystems of two artisanal cheesemaking plants, with the goal of elucidating how the processing environment influences microbial community assemblages. Results demonstrate that fermentation-associated microbes dominated most surfaces, primarily Debaryomyces and Lactococcus, indicating that establishment of these organisms on processing surfaces may play an important role in microbial transfer, beneficially directing the course of sequential fermentations. Environmental organisms detected in processing environments dominated the surface microbiota of washed-rind cheeses maturing in both facilities, demonstrating the importance of the processing environment for populating cheese microbial communities, even in inoculated cheeses. Spatial diversification within both facilities reflects the functional adaptations of microbial communities inhabiting different surfaces and the existence of facility-specific "house" microbiota, which may play a role in shaping site-specific product characteristics.

A comparison of two probiotic strains of bifidobacteria in premature infants.

OBJECTIVE: To determine the impact of 2 probiotic bifidobacteria on the fecal microbiota of premature infants fed either human milk or formula. STUDY DESIGN: In the first of two phase 1 clinical trials, 12 premature infants receiving formula feedings were assigned randomly to receive either Bifidobacterium longum ssp infantis or Bifidobacterium animalis ssp lactis in increasing doses during a 5-week period. In the second, 9 premature infants receiving their mother's milk received each of the two bifidobacteria for 2 weeks separated by a 1-week washout period. Serial stool specimens from each infant were analyzed by terminal restriction fragment-length polymorphism and quantitative polymerase chain reaction for bacterial composition. RESULTS: Among the formula-fed infants, there was a greater increase in fecal bifidobacteria among infants receiving B infantis (Binf) than those receiving B lactis (Blac). This difference was most marked at a dose of 1.4 × 10(9) colony-forming units twice daily (P < .05). Bacterial diversity improved over dose/time in those infants receiving Binf. Among the human milk-fed infants, greater increases in fecal bifidobacteria and decreases in γ-Proteobacteria followed the administration of Binf than Blac. The B longum group (which includes Binf but not Blac) was the dominant bifidobacteria among the human milk-fed infants, regardless of the probiotic administered. CONCLUSIONS: Binf was more effective at colonizing the fecal microbiota than Blac in both formula-fed and human milk-fed premature infants. The combination of human milk plus Binf resulted in the greatest fecal levels of bifidobacteria.