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

Bolyen, Evan; Rideout, Jai Ram; Dillon, Matthew R.; Bokulich, Nicholas A.; Abnet, Christian C.; Al‐Ghalith, Gabriel A.; Alexander, Hattie E.; Alm, Eric J.; Arumugam, Manimozhiyan; Asnicar, Francesco; Bai, Yang; Bisanz, Jordan E.; Bittinger, Kyle; Brejnrod, Asker; Brislawn, Colin; Brown, Calvin; Callahan, Benjamin J.; Caraballo‐Rodríguez, Andrés Mauricio; Chase, John; Cope, Emily K.; Ricardo-da-Silva, Jorge M.; Dorrestein, Pieter C.; Douglas, Gavin M.; Durall, Daniel M.; Duvallet, Claire; Edwardson, Charlotte L.; Ernst, Madeleine; Estaki, Mehrbod; Fouquier, Jennifer; Gauglitz, Julia M.; Gibson, Deanna L.; González, Antonio G.; Gorlick, Kestrel; Guo, Jiarong; Hillmann, Benjamin; Holmes, Susan; Holste, Hannes; Huttenhower, Curtis; Huttley, Gavin A.; Janssen, Stefan; Jarmusch, Alan K.; Jiang, Lingjing; Kaehler, Benjamin; Kang, Kyo Bin; Keefe, Christopher R; Keim, Paul; Kelley, Scott T.; Knights, Dan; Koester, Irina; Kościółek, Tomasz; Kreps, Jorden; Langille, Morgan G. I.; Lee, Joslynn; Ley, Ruth E.; Liu, Yong‐Xin; Loftfield, Erikka; Lozupone, Catherine; Maher, Massoud; Marotz, Clarisse; Martin, Bryan D.; McDonald, Daniel; McIver, Lauren J.; Melnik, Alexey V.; Metcalf, Jessica L.; Morgan, Sydney; Morton, Jamie; Naimey, Ahmad Turan; Navas-Molina, José A.; Nothias, Louis Félix; Orchanian, Stephanie B.; Pearson, Talima; Peoples, Samuel L; Petras, Daniel; Preuss, Mary L.; Pruesse, Elmar; Rasmussen, Lasse Buur; Rivers, Adam R.; Robeson, Michael S.; Rosenthal, Patrick; Segata, Nicola; Shaffer, Michael J.; Shiffer, Arron; Sinha, Rashmi; Song, Se Jin; Spear, John R.; Swafford, Austin D.; Thompson, Luke R.; Torres, Pedro J.; Trinh, Pauline; Tripathi, Anupriya; Turnbaugh, Peter J.; Ul-Hasan, Sabah; Hooft, Justin J. J. van der; Vargas, Fernando; Vázquez-Baeza, Yoshiki; Vogtmann, Emily; Hippel, Max von; Walters, William A.; Wan, Yunhu; Wang, Mingxun; Warren, Jonathan; Weber, Kyle C.; Williamson, Chase HD; Willis, Amy; Xu, Zhenjiang; Zaneveld, Jesse; Zhang, Yilong; Zhu, Qiyun; Knight, Rob; Caporaso, J. Gregory

doi:10.7287/peerj.preprints.27295v2

Cited by 528 publications

(491 citation statements)

References 7 publications

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“…Alpha diversity was determined using the Shannon Diversity Index and was calculated by Illumina RDP Control Software (Illumina, San Diego, CA, United States). Beta diversity of community sequencing was determined with Bray-Curtis dissimilarity (Anderson, 2001) using a one-way ANOVA (QIIME 2.0) (Bolyen et al, 2018). A t-test (Microsoft Excel) was done to compare differences in the percent phyla identified.…”

Section: Discussionmentioning

confidence: 99%

Microbiological and Nutritional Analysis of Lettuce Crops Grown on the International Space Station

Khodadad¹,

Hummerick²,

Spencer³

et al. 2020

Front. Plant Sci.

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Section: Discussionmentioning

confidence: 99%

Microbiological and Nutritional Analysis of Lettuce Crops Grown on the International Space Station

Khodadad¹,

Hummerick²,

Spencer³

et al. 2020

Front. Plant Sci.

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“…Different samples were de-multiplexed using the index reads. Amplicon sequencing variants (ASVs) were then inferred from the unmerged pair-end sequences using the DADA2 plugin within QIIME2 version 2018.6 16,17 . The forward reads were trimmed at 165 bp and the reverse reads were trimmed at 140 bp.…”

Section: Methodsmentioning

confidence: 99%

“…Only the target region of the 16S rRNA gene was used to train the classifier. Rarefaction analysis was performed within QIIME2 17 .…”

Section: Methodsmentioning

confidence: 99%

Systematic mapping of drug metabolism by the human gut microbiome

Chankhamjon

Javdan

Lopez

et al. 2019

Preprint

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25The human gut microbiome harbors hundreds of bacterial species with 26 diverse biochemical capabilities, making it one of nature's highest density, 27 highest diversity bioreactors. Several drugs have been previously shown to be 28 directly metabolized by the gut microbiome, but the extent of this phenomenon 29 has not been systematically explored. Here, we develop a systematic screen for 30 mapping the ability of the complex human gut microbiome to biochemically 31 transform small molecules (MDM-Screen), and apply it to a library of 575 clinically 32 used oral drugs. We show that 13% of the analyzed drugs, spanning 28 33 pharmacological classes, are metabolized by a single microbiome sample. In a 34 proof-of-principle example, we show that microbiome-derived metabolism occurs 35 in vivo, identify the genes responsible for it, and provide a possible link between 36 its consequences and clinically observed features of drug bioavailability and 37 toxicity. Our findings reveal a previously underappreciated role for the gut 38 microbiome in drug metabolism, and provide a comprehensive framework for 39 characterizing this important class of drug-microbiome interactions. 40 41 42 43 44 45 46 47iii) a defined mouse colonization assay for assessing the effect of the microbiome on the 94 pharmacokinetics of selected drugs. Using MDM-Screen with 575 clinically used, orally 95 administered, small molecule drugs, we discovered that 13% of them can be subject to 96 MDM. As a proof-of-principle example, we selected one of these transformations -97 MDM deglycosylation of fluoropyrimidines -for further functional investigations. We 98 identify microbiome-derived species and enzymes responsible for this transformation, 99show that it occurs in vivo in a microbiome-dependent manner, and provide evidence 100 that its consequences may explain outcomes already observed in the clinic. Our screen 101 described here, and the findings obtained from it represent the first systematic map of 102 microbiome-derived metabolism of clinically used drugs, and provide a framework for 103incorporating an "MDM" module in future drug development pipelines.

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“…QIIME2 version 2018.4.0 was used for analysis of the Illumina data (33). Amplicon sequence variant (ASV) assignment was completed using the dada2 plugin (34) and a ASV table produced using the feature-table plugin (35).…”

Section: Amplicon Sequence Variant Identification and Taxonomy Assignmentioning

confidence: 99%

Development of the Ileal Microbiota in Three Broiler Breeds

et al. 2020

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The development and succession of the microbiota in ileal mucus and lumen samples from three breeds of broiler chicken (Cobb 500, n = 36; Hubbard JA87, n = 38; and Ross 308, n = 36) was observed between 3 and 42 days post hatch (d.p.h). Chicks were housed in the same room of a climate-controlled, biosecure chicken housing unit. Between 0 and 14 d.p.h, chicks were kept in three circular brooder pens ensuring a mixture of breeds in each brooder. From 22 d.p.h, chicks were removed from the brooders and kept in the same room. DNA was extracted from a pooled sample of ileal mucus and luminal contents taken from five birds of each breed at 3, 7, 14, 21, 28, and 42 d.p.h. High-throughput Illumina sequencing was performed for the V4 hypervariable region of the 16S rRNA gene. The initial microbiota in the ileum varied between breeds. The common features were a low diversity and general dominance by one or two taxa such as Enterococcus or Escherichia with relatively low numbers of Lactobacillus. Escherichia became the most abundant genus in samples where Enterococcus was previously the dominant taxa. The next phase of development was marked by an increase in the abundance of Candidatus Arthromitus in the mucus and Lactobacillus in the lumen. The high abundance of Candidatus Arthromitus persisted between 7 and 14 d.p.h after which Lactobacillus became the most abundant genus in both the mucus and lumen. Dominance of the ileal microbiota by Lactobacillus was a transient feature. By 42 d.p.h, the relative abundance of Lactobacillus had fallen while a range of other taxa including Escherichia, Turicibacter, and members of Clostridiales increased. This general pattern was followed by all breeds, however, the rate at which succession occurred differed as Ross matured quicker than Cobb with Hubbard as an intermediate.

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

Cited by 528 publications

References 7 publications

Microbiological and Nutritional Analysis of Lettuce Crops Grown on the International Space Station

Microbiological and Nutritional Analysis of Lettuce Crops Grown on the International Space Station

Systematic mapping of drug metabolism by the human gut microbiome

Development of the Ileal Microbiota in Three Broiler Breeds

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