The adaptation of terrestrial life to extra-terrestrial environments remains a key concern of space biology research. We currently study microbial communities of extreme environments as models for successful adaptation to outer space conditions. Nevertheless, knowledge of microbial adaptation is incomplete. Most extreme environmental taxa are unknown, difficult to culture, and have uncharacterized gene functions. We recently identified hubs of unknown species by applying community network analysis to a large 16S rRNA dataset of extreme aquatic environmental samples. In this project, we will be using these 16S rRNA sequences and manually curated metagenome databases to discover and infer function of novel adaptation genes and pathways inherent to extreme environments. Under-represented STEM students will be extensively trained in computational and microbial genomics methods, particularly in mining metagenomes and searching for novel biological pathways of survival. Students will develop new skillsets in Big Data analysis and artificial intelligence, gaining knowledge of both biological algorithms and extreme adaptation mechanisms.