bioBakery: a meta’omic analysis environment

McIver, Lauren J.; Abu-Ali, Galeb; Franzosa, Eric A.; Schwager, Randall; Morgan, Xochitl C.; Waldron, Levi; Segata, Nicola; Huttenhower, Curtis

doi:10.1093/bioinformatics/btx754

Cited by 253 publications

(227 citation statements)

References 10 publications

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“…To the extent possible, multiple molecular profiles were generated from the same sets of samples, including stool metagenomes, metatranscriptomes 73 , metaproteomes, viromes, metabolomes 74,75 , host exomes, epigenomes, transcriptomes, and serological profiles, among others, allowing concurrent changes to be observed in multiple types of host and microbial molecular and clinical activity over time. Protocols and results from the study, further information about its infrastructure, and both raw and processed 76,77 data products are available through the IBDMDB data portal (http://ibdmdb.org), from the HMP2 Data Coordination Center (DCC; http://ihmpdcc.org), and in the accompanying manuscript 49 .…”

Section: The Gut Microbiome and Inflammatory Bowel Diseasementioning

confidence: 99%

The Integrative Human Microbiome Project

2019

Nature

850

373

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The Integrative Human Microbiome Project the integrative HMP (iHMP) research Network consortium* The NIH Human Microbiome Project (HMP) has been carried out over ten years and two phases to provide resources, methods, and discoveries that link interactions between humans and their microbiomes to health-related outcomes. The recently completed second phase, the Integrative Human Microbiome Project, comprised studies of dynamic changes in the microbiome and host under three conditions: pregnancy and preterm birth; inflammatory bowel diseases; and stressors that affect individuals with prediabetes. The associated research begins to elucidate mechanisms of hostmicrobiome interactions under these conditions, provides unique data resources (at the HMP Data Coordination Center), and represents a paradigm for future multi-omic studies of the human microbiome.

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Section: The Gut Microbiome and Inflammatory Bowel Diseasementioning

confidence: 99%

The Integrative Human Microbiome Project

2019

Nature

850

373

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“…Taxonomic pro les were generated with the bioBakery UPARSE [36] 16S work ow [37] v0.12.1. In brief, paired-end reads were demultiplexed using EA-Utils [38].…”

Section: Sequencing Data Analysismentioning

confidence: 99%

Whole microbial community viability is not quantitatively reflected by propidium monoazide sequencing approach

Wang

Yan

Thompson

et al. 2020

Preprint

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Background: High-throughput sequencing provides a powerful window into the structural and functional profiling of microbial communities, but it is unable to characterize only the viable portion of microbial communities at scale. There is as yet not one best solution to this problem. Previous studies have established viability assessments using propidium monoazide (PMA) treatment coupled with downstream molecular profiling (e.g. qPCR or sequencing). While these studies have met with moderate success, most of them focused on the resulting “viable” communities without systematic evaluations of the technique. Here, we present our work to rigorously benchmark “PMA-seq” (PMA treatment followed by 16S rRNA gene amplicon sequencing) for viability assessment in synthetic and realistic microbial communities. Results: PMA-seq was able to successfully reconstruct simple synthetic communities comprising viable/heat-killed Escherichia coli and Streptococcus sanguinis . However, in realistically complex communities (computer screens, computer mice, soil and human saliva) with E. coli spike-in controls, PMA-seq did not accurately quantify viability, with its performance largely affected by community properties such as initial biomass, sample types and compositional diversity. We then applied this technique to environmental swabs from the Boston subway system. Several taxa differed significantly after PMA treatment, while not all microorganisms responded consistently. To elucidate the “PMA-responsive” microbes, we compared our results with previous PMA-based studies and found that PMA-responsiveness varied widely when microbes were sourced from different ecosystems but were reproducible within similar environments across studies. Conclusions: This study provides a comprehensive evaluation of PMA-seq exploring its quantitative accuracy in synthetic and complex microbial communities, where the technique was effective for semi-quantitative purposes in simple synthetic communities, but provided only qualitative assessments in realistically complex community samples.

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“…To account for potential confounding factors, we used the Multivariate Association with Linear Model, MaAsLin, in R [40], which allows for the use of covariates in the model. In brief, MaAsLin fits a linear model for each species and the variable of interest, here PCOS, after arcsin-squareroot transformation of the proportional values of the species.…”

Section: Association Analyses Between Individual Species Pcos and Homentioning

confidence: 99%

“…In brief, MaAsLin fits a linear model for each species and the variable of interest, here PCOS, after arcsin-squareroot transformation of the proportional values of the species. This transformation has been shown to stabilise variance and normalise proportional data well [40]. The method can also include a boosting step to select factors among a large set of variables to be associated with the species.…”

Section: Association Analyses Between Individual Species Pcos and Homentioning

confidence: 99%

Bifidobacteriumis enriched in gut microbiome of Kashmiri women with polycystic ovary syndrome

Hassan

Draisma

et al. 2019

Preprint

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Polycystic ovary syndrome (PCOS) is a common endocrine condition in women of reproductive age understudied in non-European populations. In India, PCOS affects the life of up to 19.4 million women of age 14-25 years. Gut microbiome composition might contribute to PCOS susceptibility.We profiled the microbiome in DNA isolated from faecal samples by 16S rRNA sequencing in 19/20 women with/without PCOS from Kashmir, India. We assigned genera to sequenced species with an average 121k reads depth and included bacteria detected in at least 1/3 of the subjects or with average relative abundance ≥0.1%. We compared the relative abundances of 40/58 operational taxonomic units in family/genus level between cases and controls, and in relation to 33 hormonal and metabolic factors, by multivariate analyses adjusted for confounders, and corrected for multiple testing. Seven genera were significantly enriched in PCOS cases: Sarcina, Alkalibacterium and Megasphaera, and previously reported for PCOS Bifidobacterium, Collinsella, Paraprevotella and Lactobacillus. We identified significantly increased relative abundance of Bifidobacteriaceae (median 6.07% vs. 2.77%) and Aerococcaceae (0.03% vs. 0.004%), whereas we detected lower relative abundance Peptococcaceae (0.16% vs. 0.25%) in PCOS cases. For the first time, we identified a significant direct association between butyrate producing Eubacterium and follicle-stimulating hormone levels. We observed increased relative abundance of Collinsella and Paraprevotella with higher fasting blood glucose levels, and Paraprevotella and Alkalibacterium with larger hip and waist circumference, and weight. We show a relationship between gut microbiome composition and PCOS linking it to specific reproductive health metabolic and hormonal predictors in Indian women.

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bioBakery: a meta’omic analysis environment

Cited by 253 publications

References 10 publications

The Integrative Human Microbiome Project

The Integrative Human Microbiome Project

Whole microbial community viability is not quantitatively reflected by propidium monoazide sequencing approach

Bifidobacteriumis enriched in gut microbiome of Kashmiri women with polycystic ovary syndrome

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