Although the vast majority of microbes in nature resist laboratory cultivation, they represent an almost limitless reservoir of genetic diversity and metabolic innovation. Next generation sequencing technologies are rapidly expanding our capacity to access genotypic and phenotypic information directly from environmental samples. However, to effectively interpret and apply this increasing volume of information, new analytical tools and services must be developed with the end user in mind. Here, I explore problems and solutions in environmental sequence analysis spanning different levels of biological organization from genomes to biomes. I highlight emerging open source tools for integrating and visualizing multimolecular (DNA, RNA and protein) and environmental parameter data and consider the future of data intensive computation and environmental sensing as it relates to pathway reconstruction, ecosystem modeling and synthetic ecology.
Dr. Steven Hallam is a University of California Santa Cruz and MIT trained molecular biologist, microbial ecologist, entrepreneur, and innovator with over 20 years experience in field and laboratory research at disciplinary interfaces. He is an Associate Professor in the Department of Microbiology and Immunology, Canada Research Chair in Environmental Genomics and a scholar in the Canadian Institute for Advanced Research (CIFAR) integrated microbial biodiversity program. He is also a program faculty member in the Bioinformatics and Genome Sciences and Technology training programs at UBC and Peter Wall Scholar in residence. Dr. Hallam currently directs ECOSCOPE an NSERC CREATE industrial stream training program in support of the emerging bioeconomy. Dr. Hallam’s current research intersects microbial ecology, biological engineering and bioinformatics with specific emphasis on the creation of functional screens and computational tools that reveal hidden metabolic powers of uncultivated microbial communities. His laboratory has developed MetaPathways, a modular annotation and analysis pipeline to predict metabolic interactions from environmental sequence information. Other research areas include single-cell genome sequencing and biosensor development for environmental monitoring and enzyme discovery.
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