No abstract

We present QIIME 2, an open-source microbiome data science platform accessible to users spanning the microbiome research ecosystem, from scientists and engineers to clinicians and policy makers. QIIME 2 provides new features that will drive the next generation of microbiome research. These include interactive spatial and temporal analysis and visualization tools, support for metabolomics and shotgun metagenomics analysis, and automated data provenance tracking to ensure reproducible, transparent microbiome data science.

In the version of this article initially published, some reference citations were incorrect. The three references to Jupyter Notebooks should have cited Kluyver et al. instead of Gonzalez et al. The reference to Qiita should have cited Gonzalez et al. instead of Schloss et al. The reference to mothur should have cited Schloss et al. instead of McMurdie & Holmes. The reference to phyloseq should have cited McMurdie & Holmes instead of Huber et al. The reference to Bioconductor should have cited Huber et al. instead of Franzosa et al. And the reference to the biobakery suite should have cited Franzosa et al. instead of Kluyver et al. The errors have been corrected in the HTML and PDF versions of the article.

We present QIIME 2, an opensource microbiome data science platform accessible to users spanning the microbiome research ecosystem, from scientists and engineers to clinicians and policy makers. QIIME 2 provides new features that will drive the next generation of microbiome research. These include interactive spatial and temporal analysis and visualization tools, support for metabolomics and shotgun metagenomics analysis, and automated data provenance tracking to ensure reproducible, transparent microbiome data science.PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.27295v2 | CC BY 4.0 Open Access | rec:

We present QIIME 2, an open-source microbiome data science platform accessible to users spanning the microbiome research ecosystem, from scientists and engineers to clinicians and policy makers. QIIME 2 provides new features that will drive the next generation of microbiome research. These include interactive spatial and temporal analysis and visualization tools, support for metabolomics and shotgun metagenomics analysis, and automated data provenance tracking to ensure reproducible, transparent microbiome data science.

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No abstract

The microbial consortium of wine fermentations is highly dependent upon winemaking decisions made at crush, including the decision to inoculate and the decision to add sulfur dioxide (SO2) to the must. To investigate this, Chardonnay grape juice was subjected to two inoculation treatments (uninoculated and pied de cuve inoculation) as well as two SO2 addition concentrations (0 and 40 mg/L). The bacterial communities, fungal communities and Saccharomyces populations were monitored throughout fermentation using culture-dependent and culture-independent techniques. After fermentation, the wines were evaluated by a panel of experts. When no SO2 was added, the wines underwent alcoholic fermentation and malolactic fermentation simultaneously. Tatumella bacteria were present in significant numbers, but only in the fermentations to which no SO2 was added, and were likely responsible for the malolactic fermentation observed in these treatments. All fermentations were dominated by a genetically diverse indigenous population of Saccharomyces uvarum, the highest diversity of S. uvarum strains to be identified to date; 150 unique strains were identified, with differences in strain composition as a result of SO2 addition. This is the first report of indigenous S. uvarum strains dominating and completing fermentations at a commercial winery in North America.