Explicet: graphical user interface software for metadata-driven management, analysis and visualization of microbiome data

Robertson, Charles E.; Harris, J. Kirk; Wagner, Brandie D.; Granger, David; Browne, Kathy; Tatem, Beth; Feazel, Leah M.; Park, Kristin; Pace, Norman R.; Frank, Daniel N.

doi:10.1093/bioinformatics/btt526

Cited by 245 publications

(187 citation statements)

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“…Comparison of the relative abundances of the OTUs between groups was performed using a Wilcoxon test with a continuity correction using a software package, Explicet, specifically addressed to analyse microbiome data [16]. α-and β-diversities were achieved by QIIME: α-diversity using a nonparametric t-test with a default number of 999 Monte Carlo permutations, and β-diversity using the ANOSIM statistical method with 99 permutations.…”

Section: Resultsmentioning

confidence: 99%

Intermittent hypoxia alters gut microbiota diversity in a mouse model of sleep apnoea

et al. 2014

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We assessed whether intermittent hypoxia, which emulates one of the hallmarks of obstructive sleep apnoea (OSA), leads to altered faecal microbiome in a murine model.In vivo partial pressure of oxygen was measured in colonic faeces during intermittent hypoxia in four anesthetised mice. 10 mice were subjected to a pattern of chronic intermittent hypoxia (20 s at 5% O 2 and 40 s at room air for 6 h·day −1 ) for 6 weeks and 10 mice served as normoxic controls. Faecal samples were obtained and microbiome composition was determined by 16S rRNA pyrosequencing and bioinformatic analysis by Quantitative Insights into Microbial Ecology.Intermittent hypoxia exposures translated into hypoxia/re-oxygenation patterns in the faeces proximal to the bowel epithelium (<200 μm). A significant effect of intermittent hypoxia on global microbial community structure was found. Intermittent hypoxia increased the α-diversity (Shannon index, p<0.05) and induced a change in the gut microbiota (ANOSIM analysis of β-diversity, p<0.05). Specifically, intermittent hypoxia-exposed mice showed a higher abundance of Firmicutes and a smaller abundance of Bacteroidetes and Proteobacteria phyla than controls.Faecal microbiota composition and diversity are altered as a result of intermittent hypoxia realistically mimicking OSA, suggesting the possibility that physiological interplays between host and gut microbiota could be deregulated in OSA. @ERSpublications Faecal microbiota composition and diversity are altered due to intermittent hypoxia mimicking OSA in a murine model

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Section: Resultsmentioning

confidence: 99%

Intermittent hypoxia alters gut microbiota diversity in a mouse model of sleep apnoea

et al. 2014

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“…Shannon diversity index, an ecologic parameter that takes into account community richness and evenness, was calculated in Explicet (27) using rarefaction to the number of sequences in the smallest library (28,29). Communities across sample types within a subject were compared using Shannon Beta, a measure of b-diversity (30).…”

Section: Original Researchmentioning

confidence: 99%

Assessment of Airway Microbiota and Inflammation in Cystic Fibrosis Using Multiple Sampling Methods

et al. 2015

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Rationale: Oropharyngeal (OP) swabs and induced sputum (IS) are used for airway bacteria surveillance in nonexpectorating children with cystic fibrosis (CF). Molecular analyses of these airway samples detect complex microbial communities. However, the optimal noninvasive sampling approach for microbiota analyses and the clinical relevance of microbiota, particularly its relationship to airway inflammation, is not well characterized.Objectives: The goals of this study were to compare molecular analyses of concurrently collected saliva, OP swabs, IS, and expectorated sputum (ES) from children with CF and to determine the association between microbiota, lung function, and airway inflammation.Methods: Saliva, OP swabs, IS, and ES were collected from 16 children with CF. Spirometry was performed.Measurements and Main Results: Respiratory and saliva samples (n = 61) were sequenced for bacterial microbial communities, and total and CF-specific bacterial quantitative PCR assays were performed. Airway samples underwent conventional culture for CF-specific pathogens. Neutrophil elastase, IL-1b, IL-1ra, IL-6, Il-8, TNF-a, and vascular endothelial growth factor were measured in ES and IS. Sequencing results from individual subjects were similar across samples, with greater between-subject than within-subject variation. However, Pseudomonas and Staphylococcus were detected in higher relative abundance from lower airways (ES and IS) compared with paired upper airway samples (OP and saliva). Pseudomonas, Staphylococcus, and Enterobacteriaceae correlated with increased airway inflammation. Divergence between microbiota in upper airway compared with lower airway samples, indicating greater differences between communities, was associated with increased sputum neutrophil elastase.Conclusions: Bacteria detected in IS samples resemble ES samples, whereas OP samples may underrepresent bacteria associated with airway inflammation. Divergence of lower airway communities from upper airway was associated with airway inflammation and may portend disease progression.

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“…Further, sequences from the specific genera of interest were extracted from the sequence files and then blasted against the NCBI database (accessed 17 October 2014) to allow further phylogenetic discrimination between closely related taxa. Exploratory and statistical analyses of the data were carried out using QIIME, PASW Statistics, version 18 (SPSS, Inc., Chicago, IL), and Explicet (20). Jackknifed trees using the unweighted-pair group method using average linkages (UPGMA) based on weighted hierarchal clustering (6,670 replicate sequences; E value, 10) were constructed to visualize sample similarity based on phylogenetic distance between taxa (UniFrac software) (21) and were viewed using FigTree, version 1.4, software (tree.bio.ed.ac.uk/software).…”

Section: Site Descriptions (I) Wa Dwdsmentioning

confidence: 99%

Using Amplicon Sequencing To Characterize and Monitor Bacterial Diversity in Drinking Water Distribution Systems

Shaw

Monis

Weyrich

et al. 2015

Appl Environ Microbiol

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b Drinking water assessments use a variety of microbial, physical, and chemical indicators to evaluate water treatment efficiency and product water quality. However, these indicators do not allow the complex biological communities, which can adversely impact the performance of drinking water distribution systems (DWDSs), to be characterized. Entire bacterial communities can be studied quickly and inexpensively using targeted metagenomic amplicon sequencing. Here, amplicon sequencing of the 16S rRNA gene region was performed alongside traditional water quality measures to assess the health, quality, and efficiency of two distinct, full-scale DWDSs: (i) a linear DWDS supplied with unfiltered water subjected to basic disinfection before distribution and (ii) a complex, branching DWDS treated by a four-stage water treatment plant (WTP) prior to disinfection and distribution. In both DWDSs bacterial communities differed significantly after disinfection, demonstrating the effectiveness of both treatment regimes. However, bacterial repopulation occurred further along in the DWDSs, and some end-user samples were more similar to the source water than to the postdisinfection water. Three sample locations appeared to be nitrified, displaying elevated nitrate levels and decreased ammonia levels, and nitrifying bacterial species, such as Nitrospira, were detected. Burkholderiales were abundant in samples containing large amounts of monochloramine, indicating resistance to disinfection. Genera known to contain pathogenic and fecal-associated species were also identified in several locations. From this study, we conclude that metagenomic amplicon sequencing is an informative method to support current compliance-based methods and can be used to reveal bacterial community interactions with the chemical and physical properties of DWDSs.T ransmission of pathogens via contaminated water is a significant cause of illness worldwide. It has been estimated that one-third of gastrointestinal illnesses are caused by contaminated drinking water (1), and 4% of all deaths worldwide are due to polluted drinking water and poor sanitation (2). In developed nations water quality assessments and treatment facilities have been introduced to reduce microbial contamination, resulting in a significant reduction in drinking water-related illnesses and deaths. Water treatment commonly involves the reduction of organics and other contaminants via coagulation and sedimentation, separation of any remaining solids via filtration, and finally disinfection via chemical oxidants or ultraviolet (UV) radiation. The addition of chemical oxidants such as chlorine and monochloramine is the most common method of drinking water disinfection (3). The level of treatment required varies from system to system, with some drinking water distribution systems (DWDSs) receiving only one or two levels of treatment, while others require multiple treatments to create water suitable for end use.Currently, most drinking water quality assessments do not directly taxonomically ide...

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Explicet: graphical user interface software for metadata-driven management, analysis and visualization of microbiome data

Cited by 245 publications

References 14 publications

Intermittent hypoxia alters gut microbiota diversity in a mouse model of sleep apnoea

Intermittent hypoxia alters gut microbiota diversity in a mouse model of sleep apnoea

Assessment of Airway Microbiota and Inflammation in Cystic Fibrosis Using Multiple Sampling Methods

Using Amplicon Sequencing To Characterize and Monitor Bacterial Diversity in Drinking Water Distribution Systems

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