Bioinformatics Core

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SUMMARY The development of antimicrobial resistance involves the rise of heterogeneity in populations of microbes by uncertain mechanisms. This Unit is focused on the understanding the rise of cell- states that we call enablers that give rise to treatment failure. Identifying these cell states requires the development, sharing, implementation support, and analytical training of a broad suite of genomics and bioinformatics methods for each scientific project. The key function of this Core is to integrate methods, data, and support team members with their analysis goals. This Genomics and Bioinformatics core commits to provide this support and analytical leadership by establishing rigorous workflows for a wide range of nucleic acid library preparations. In addition, we will develop and share a range of innovative bioinformatic analyses methods for assembly, quantitative read-mapping, community profiling, and portable bacterial genome nomenclature. Most importantly for the broader impact of this project, we will enable iterative, reproducible inquiry of ‘omics data with bioinformatics training for trainees, staff, and collaborators throughout the team. In Aim 1, we develop and provide methods to analyze genome fragments or amplicons, including gDNA sequencing, barcode sequencing, Tn-Seq, droplet-TnSeq (dTnseq), Deplete-seq (called Enabler-seq here) and CRISPRi/Tn-seq. We will also continue development and economization of RNAseq methods such as RNAtag-Seq, dual-host-microbe RNA-seq (dRNA-Seq), 3’-end map- sequencing (3pMap / Term-Seq), and will develop the use of direct RNA sequencing to identify transcript modifications or isoforms that drive enabler types. In Aim 2, we develop and support implementation of a variety of analysis methods to turn these ‘omics data into knowledge, including an innovative pipeline called Aerobio that addresses the challenge of integrating multiple data and analysis streams and new inference platforms like LOLIPoP and BFClust. In Aim 3 we focus on democratizing data exploration throughout the team and ultimately for the broader research community by offering training on portable methods. These efforts include a new, flexible ortholog identification tool with a graphical interface (OrthoPathDB) built upon our published ShinyOmics, shared resources for distributed installation, and regular training in genomic DNA analysis, RNAseq, amplicon sequencing, and host immunity - microbe interactions. In summary, this Core will consistently generate high-quality data and provide unfettered access to both wet- bench and bioinformatic methodology, as well as their workflow status, via open sharing and training.