Being “hardware agnostic”

1. Allow any PreMiEr researcher (or other interested scientist) to faithfully reproduce analyses regardless of hardware
2. Provide virtualized containers for on-campus and other systems, including a primary system at UNC-Charlotte, the ViCAR system at North Carolina A&T, and the cloud

Environments in indoor spaces often reflect low biomass conditions, or spaces where the number of microbes is relatively low. Accurately sampling and sequencing the DNA or RNA of these microbes and distinguising these communities from contaminants is a major concern.  This project aims to develop the next generation of low-biomass microbial measurements that are effective, economical, and relevant to the wide spectrum of built environment sample types.

Microbiome research depends on the microbial genomes in databases. Microbiome sequence data that cannot be mapped to a genome in a database is biological “dark matter” and it is difficult or impossible to derive biological meaning from this data. This project aims to determine optimal sequencing and analysis approaches for different sample types and to determine, for each sample type, which sequencing approach is most amenable to generating high quality metagenome-assembled genomes (MAGs).

This project will determine the computational assets and needs across the center and develop a comprehensive PreMiEr computational research and training infrastructure to support bioinformatics and microbiome research. This will be accomplished through an assessment of the computational resources within PreMiEr and the development of bioinformatic workflows with training modules accessible to all participants.