Microorganisms Genome Enrichment and Amplification Sequencing (MGEAS)

Recent evidence shows that the cleanrooms of Jet Propulsion Laboratory environments, such as floors and hardware surfaces, could harbor various microorganisms, and a comprehensive metagenomics framework to characterize organisms relevant to planetary protection is needed. Current metagenomics practices for microbe detection in low biomass samples generally do not fit well with NASA needs, due to high requirements in DNA concentration, small sample processing volumes, variability, and high predictive errors. MGEAS addresses these issues with three modules (1) A sampling or filtration unit that process larger volumes of input solutions, (2) DNA preparations, enrichment, and amplifications followed by NGS sequencing, (3) Bioinformatics pipeline optimization for reads classification and genome assembly. As part of the phase I project ChromoLogic i) successfully evaluated two state-of-the-art genome amplification or enrichment techniques for NGS library preparation. ii) optimized kmers and various bioinformatics parameters for microbial taxa classification based on raw reads and iii) provided taxa reports for JPL environmental samples (wipes and swabs) and identified taxa with radiation, disinfectant resistance. In Phase II we propose to combine our achievements with a) the novel use of SMART accessory blocks for lab-work automations, and various techniques to improve nucleic acids yield and assay repeatability, b) state of the art DNA preparations, enrichment and amplifications followed by NGS sequencing, and c) Bioinformatics pipeline optimization for reads classification, genome assembly and adjacent DNA linked reads sequencing (Hi-C) for radiation/disinfectant resistant elements origin tracing (in species and environments). We will also expand our statistical modeling tests to improve accuracy and sensitivity of assays to fit NASA needs and we will build interactive software visualization tools for easier user navigation of taxa data and sample statistics.