Single-cellular organisms (microbes) represent a vast component of the diversity of life on Earth and perform an amazing array of biological functions. They rarely live or act alone and instead exist in complex communities composed of many interacting species that make up the microbiome. This award supports the development of the next generation of Quantitative Insights Into Microbial Ecology (QIIME, pronounced 'chime'), a free and open source software platform for analyzing microbiomes based on DNA sequencing data. Microbiome science is in a transformation from being descriptive and technically challenging, to becoming hypothesis-driven, actionable, and technically straight-forward, in part enabled by QIIME. We now know that the traditional approach for studying microbial communities, which relied on culturing microbes in the lab, is insufficient because we don't know the conditions required for the growth of most microbes. Recent advances link microbiomes to functional processes via 'culture independent' techniques, such as sequencing fragments of microbial genomes, and then using those fragments as 'molecular fingerprints' to profile the microbiome. The bottleneck in microbiome analysis is not DNA sequencing, but in interpreting the large quantities of sequence data generated. QIIME 2 will advance knowledge of microbiomes by helping users derive insight through interactive exploratory analysis capabilities, understand the underlying methods, and report their results in ways accessible to end users from outside of the field, including physicians, engineers and policymakers who urgently need access to conclusions drawn from studies of complex microbial ecosystems. Societal benefits range from global to personal (from understanding cycling of biologically essential nutrients, such as carbon and nitrogen in the environment to curing disease, including obesity and cancer). QIIME has been cited over 4,000 times and has active user and developer communities. Educational workshops on QIIME are taught approximately monthly in the USA and around the world.

At its core, QIIME 2 will provide a stable application programming interface (API) relying on existing community standards for documentation, coding style, and testing. It will have a novel 'documentation-driven' graphical user interface that will make QIIME accessible to users without requiring advanced computational skills. At the same time, it will help users improve their computational skills through exposure to the underlying bioinformatics methods. QIIME 2 will have fully integrated provenance tracking, which will simplify reporting and reproducibility of bioinformatics workflows. A first-class plugin system will decentralize development by allowing outside developers to add new methods to the QIIME 2 platform. The API will also support improved integration of QIIME as a component of other widely used systems, such as Illumina BaseSpace® and Qiita, and an automatically generated command line interface will be provided for power users. QIIME 2 will have a completely redeveloped parallel framework, which will support deployment on diverse high-performance computing resources, from locally owned and operated computer clusters to commercially available cloud computing platforms. All stages of QIIME 2 development will be driven by user community input through the QIIME Forum (currently over 2500 active users) and our public GitHub repository. Further details on this project are on the QIIME website (www.qiime.org).

Agency
National Science Foundation (NSF)
Institute
Division of Biological Infrastructure (DBI)
Type
Standard Grant (Standard)
Application #
1565100
Program Officer
Peter McCartney
Project Start
Project End
Budget Start
2016-05-01
Budget End
2020-04-30
Support Year
Fiscal Year
2015
Total Cost
$525,795
Indirect Cost
Name
Northern Arizona University
Department
Type
DUNS #
City
Flagstaff
State
AZ
Country
United States
Zip Code
86011