Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2

Nature Biotechnology, Journal Year: 2019, Volume and Issue: 37(8), P. 852 - 857

Published: July 24, 2019

Language: Английский

---

RESCRIPt: Reproducible sequence taxonomy reference database management

PLoS Computational Biology, Journal Year: 2021, Volume and Issue: 17(11), P. e1009581 - e1009581

Published: Nov. 8, 2021

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

Language: Английский

---

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

Current Protocols in Bioinformatics, Journal Year: 2020, Volume and Issue: 70(1)

Published: April 28, 2020

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

Language: Английский

---

q2-longitudinal: Longitudinal and Paired-Sample Analyses of Microbiome Data

mSystems, Journal Year: 2018, Volume and Issue: 3(6)

Published: Oct. 30, 2018

Longitudinal sampling provides valuable information about temporal trends and subject/population heterogeneity. We describe q2-longitudinal, a software plugin for longitudinal analysis of microbiome data sets in QIIME 2. The availability statistics visualizations the 2 framework will make more accessible to researchers.

Language: Английский

---

Gut microbiome, big data and machine learning to promote precision medicine for cancer

Nature Reviews Gastroenterology & Hepatology, Journal Year: 2020, Volume and Issue: 17(10), P. 635 - 648

Published: July 9, 2020

Language: Английский

---

Man-made microbial resistances in built environments

Nature Communications, Journal Year: 2019, Volume and Issue: 10(1)

Published: Feb. 27, 2019

Antimicrobial resistance is a serious threat to global public health, but little known about the effects of microbial control on microbiota and its associated resistome. Here we compare present surfaces clinical settings with other built environments. Using state-of-the-art metagenomics approaches genome plasmid reconstruction, show that increased confinement cleaning loss diversity shift from Gram-positive bacteria, such as Actinobacteria Firmicutes, Gram-negative Proteobacteria. Moreover, microbiome highly maintained environments has different resistome when compared environments, well higher in genes. Our results highlight correlates an increase resistance, need for implementing strategies restore bacterial certain

Language: Английский

---

A catalogue of 1,167 genomes from the human gut archaeome

Nature Microbiology, Journal Year: 2021, Volume and Issue: 7(1), P. 48 - 61

Published: Dec. 30, 2021

The human gut microbiome plays an important role in health, but its archaeal diversity remains largely unexplored. In the present study, we report analysis of 1,167 nonredundant genomes (608 high-quality genomes) recovered from gastrointestinal tract, sampled across 24 countries and rural urban populations. We identified previously undescribed taxa including 3 genera, 15 species 52 strains. Based on distinct genomic features, justify split Methanobrevibacter smithii clade into two separate species, with one represented by 'Candidatus intestini'. Patterns derived 28,581 protein clusters showed significant associations sociodemographic characteristics such as age groups lifestyle. additionally show that archaea are characterized specific functional adaptations to host carry a complex virome. Our work expands our current understanding archaeome provides large genome catalogue for future analyses decipher impact physiology.

Language: Английский

---

Stochasticity Highlights the Development of Both the Gastrointestinal and Upper-Respiratory-Tract Microbiomes of Neonatal Dairy Calves in Early Life

Animals, Journal Year: 2025, Volume and Issue: 15(3), P. 361 - 361

Published: Jan. 27, 2025

The microbiome of dairy calves undergoes extensive change due to various forces during the first weeks life. Importantly, diseases such as bovine respiratory disease (BRD) and calf diarrhea can have profound impacts on early-life microbiome. Therefore, a longitudinal, repeated-measures pilot study was designed characterize establishment nasal fecal microbiomes calves, assess governing microbial assembly, evaluate how states impact these ecologies. Dairy (n = 19) were clinically evaluated for gastrointestinal across three beginning at age ≤ seven days old. Fecal 57) samples taken paired-end 16S rRNA gene amplicon sequencing. Taxonomy diversity analyses used microbiomes. Stochasticity determinism measured using normalized stochasticity testing (NST) Dirichlet multinomial model (DMM). All tested statistical significance. Clinical observed in 11 19 calves. BRD not independently among cohort; however, two presented clinical signs both diarrhea. Taxonomic analysis revealed that highlighted by Bacteroidaceae (40%; relative abundance), Ruminococcaceae (13%), Lachnospiraceae (10%), with changes (Kruskal–Wallis; p < 0.05) composition (PERMANOVA; 0.05). reduced but did composition. Nasal featured Moraxellaceae (49%), Mycoplasmataceae (16%), Pasteurellaceae (3%). While no seen samples, compositional (p NST metrics > 0.01) DMM stochastic, neutral theory-based assembly dynamics govern distinct populations drive community healthy diarrheic

Language: Английский

---

Machine learning to predict microbial community functions: An analysis of dissolved organic carbon from litter decomposition

PLoS ONE, Journal Year: 2019, Volume and Issue: 14(7), P. e0215502 - e0215502

Published: July 1, 2019

Microbial communities are ubiquitous and often influence macroscopic properties of the ecosystems they inhabit. However, deciphering functional relationship between specific microbes ecosystem is an ongoing challenge owing to complexity communities. This can be addressed, in part, by integrating advances DNA sequencing technology with computational approaches like machine learning. Although learning techniques have been applied microbiome data, use these remains rare, user-friendly platforms implement such not widely available. We developed a tool that implements neural network random forest models perform regression feature selection tasks on data. In this study, we analyze soil (16S rRNA gene profiles) dissolved organic carbon (DOC) data from 44-day plant litter decomposition experiment. The includes 1709 total bacterial operational taxonomic units (OTU) 300+ microcosms. Regression analysis predicted actual DOC for held-out test set 51 samples yield Pearson's correlation coefficients of.636 and.676 approaches, respectively. Important taxa identified compared results standard (indicator species analysis) used microbial ecologists. Of taxa, indicator 285 as significant determinants concentration. top ranked features determined methods, subset 86 common all techniques. Using features, prediction permutations at least equally accurate predictions using entire set. Our suggest integration multiple methods aid identification robust within complex may drive outcomes interest.

Language: Английский

---

Essential Hypertension Is Associated With Changes in Gut Microbial Metabolic Pathways: A Multisite Analysis of Ambulatory Blood Pressure

Hypertension, Journal Year: 2021, Volume and Issue: 78(3), P. 804 - 815

Published: Aug. 2, 2021

Recent evidence supports a role for the gut microbiota in hypertension, but whether ambulatory blood pressure is associated with and their metabolites remains unclear. We characterized function of microbiota, receptors untreated human hypertensive participants Australian metropolitan regional areas. Ambulatory pressure, fecal microbiome predicted from 16S rRNA gene sequencing, plasma called short-chain fatty acid, expression were analyzed 70 otherwise healthy communities. Most normotensives female (66%) compared hypertensives (35%, P <0.01), there was no difference age between groups (59.2±7.7 versus 60.3±6.6 years old). Based on machine learning multivariate covariance analyses de-noised amplicon sequence variant prevalence data, we determined that significant differences α- β-diversity metrics essential or masked hypertensives. However, select taxa specific to these groups, notably Acidaminococcus spp ., Eubacterium fissicatena, Muribaculaceae higher, while Ruminococcus eligens lower Importantly, normotensive cohorts could be differentiated based pathways metabolites. Specifically, exhibited higher acetate butyrate, immune cells expressed reduced levels acid-activated GPR43 (G-protein coupled receptor 43). In conclusion, microbial diversity did not change observed shift pathways. Hypertensive subjects had GPR43, putatively blunting response pressure-lowering

Language: Английский

---